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The cure fraction models are intended to analyze lifetime data from populations where some individuals are immune to the event under study, and allow a joint estimation of the distribution related to the cured and susceptible subjects, as opposed to the usual approach ignoring the cure rate. In situations involving small sample sizes with many censored times, the detection of nonfinite coefficients may arise via maximum likelihood. This phenomenon is commonly known as monotone likelihood (ML), occurring in the Cox and logistic regression models when many categorical and unbalanced covariates are present. An existing solution to prevent the issue is based on the Firth correction, originally developed to reduce the estimation bias. The method ensures finite estimates by penalizing the likelihood function. In the context of mixture cure models, the ML issue is rarely discussed in the literature; therefore, this topic can be seen as the first contribution of our paper. The second major contribution, not well addressed elsewhere, is the study of the ML issue in cure mixture modeling under the flexibility of a semiparametric framework to handle the baseline hazard. We derive the modified score function based on the Firth approach and explore finite sample size properties of the estimators via a Monte Carlo scheme. The simulation results indicate that the performance of coefficients related to the binary covariates are strongly affected to the imbalance degree. A real illustration, in the melanoma dataset, is discussed using a relatively novel data set collected in a Brazilian university hospital.

This study investigates the effects of simulation and Guided-inquiry strategies in elimination of students’ misconception in Biology Teaching in Senior Secondary Schools in Obio/Akpor Local Government Area in Rivers State. Four research questions and four hypotheses were formulated to guide the research. The design adopted for this study is quasi experimental pre-test, post-test control group design. The population of the study was made up of all SSIII biology students, using cluster sampling to select 150 students’ to form the sample size. The research instrument used was Ecology performance Test (EPT). Mean and standard deviation were used to answer the research questions. T-test was used to test the hypotheses. The findings among others indicated that students taught with simulation and guided inquiry teaching strategy performed better than the traditional method thereby eliminating student’s misconception on ecological concept in biology. It was recommended among others that biology teachers should be encouraged to explore the application of simulation and guided inquiring strategies in their classroom instruction.

The goal of this research is to compare multiple linear regression coefficient estimations with multicollinearity. In order to quantify the effectiveness of estimations by the mean of average mean square error, the ordinary least squares technique (OLS), modified ridge regression method (MRR), and generalized Liu-Kejian method (LKM) are compared (AMSE). For this study, the simulation scenarios are 3 and 5 independent variables with zero mean normally distributed random error of variance 1, 5, and 10, three correlation coefficient levels; i.e., low (0.2), medium (0.5), and high (0.8) are determined for independent variables, and all combinations are performed with sample sizes 15, 55, and 95 by Monte Carlo simulation technique for 1,000 times in total. As the sample size rose, the AMSE decreased. The MRR and LKM both outperformed the LSM. At random error of variance 10, the MRR is the most suitable for all circumstances.

We consider partially observed binary matched-pair data. We assume that the incomplete subjects are missing at random. Within this missing framework, we propose an EM-algorithm based approach to construct an interval estimator of the proportion difference incorporating all the subjects. In conjunction with our proposed method, we also present two improvements to the interval estimator through some correction factors. The performances of the three competing methods are then evaluated through extensive simulation. Recommendation for the method is given based on the ability to preserve type-I error for various sample sizes. Finally, the methods are illustrated in two real-world data sets. An R-function is developed to implement the three proposed methods.

A new lifetime distribution called alpha power modified Weibull (APMW) distribution based on the alpha power transformation method has been studied. Various statistical properties of the newly developed distribution including quantiles, moments, stress-strength parameter, Bonferroni and Lorentz curve, residual and reversed residual lifetime function, stress-strength parameter, entropy and order statistics have been obtained. Percentage points of the APMW distribution for different values of the parameters have been obtained. The method of maximum likelihood estimation (MLE) has been used for estimating the parameters. A simulation study has been performed to evaluate the behaviour of the MLEs in terms of the sample size n and revealed that as the value of the sample size increases the value of the mean square error decreases showing the reliability of the estimators. The efficiency and flexibility of the new distribution are illustrated by analysing three real-life data sets. In each case, the APMW distribution provides a better fit indicating that the APMW distribution is a justifiable choice for fitting the considered data sets.

Introduction Significant amount of pregnant mothers is not undergoing spontaneous onset of labour at term. The policy of cervical ripening at term will reduce the risk and their complications associated with post date pregnancies. Artificial sweeping of membranes and nitric oxide donors are useful cervical ripening methods used across the world. This study was carried out to compare the efficacy of cervical ripening by administration of intravaginal Glyceryltrinitrate plus artificial sweeping of membranes versus artificial sweeping of membranes alone. Objectives To Compare of the efficacy,the spontaneous onset of labour rate, the labour outcome, the duration from induction to the delivery time of baby and adverse maternal and fetal outcomes of cervical ripening by administrating of intravaginal Glyceryltrinitrate combined with artificial sweeping of membranes versus artificial sweeping of membranes alone. Methodology This was a double blinded randomized clinical trial carried out in a major obstetric unit in Sri Lanka.Having excluded the subjects according to the exclusion criteria, rest of the sample was divided into cases and controls. Sample size was calculated as 114 for each arm. Approval of the proposal and ethical clearance have been obtained from the board of study and ethical review committee of postgraduate institute of medicine, University of Colombo, SriLanka respectively.Sample randomization done by using stratified block randomization technique with sealed envelope. Information leaflet was given and detailed written consent was taken from the subjects prior to the recruitment. Artificial sweeping of membranes together with intravaginal Glycery ltrinitrate was inserted for the cases and artificial sweeping of membranes alone was performed for the control group. Spontaneous onset of labour, improvement of the modified Bishop’s Score and labor outcome were assessed. Data were analyzed by using SPSS software. Results Mean age, parity and gestational age were matched in both intervention and control group. Results were analyzed by SPSS software using standard statistical tools. Spontaneous onset of labour within 24 hours were significantly increased (p

Abstract Aim By means of a systematic review and network meta-analysis, this study aims to answer the following questions: (a) does the placement of a biomaterial over an extraction socket lead to better outcomes in terms of horizontal and vertical alveolar dimensional changes and percentage of new bone formation than healing without coverage? And (b) which biomaterial(s) provide(s) the better outcomes? Materials and methods Parallel and split-mouth randomized controlled trials treating ≥ 10 patients were included in this analysis. Studies were identified with MEDLINE (PubMed), Embase, Cochrane Central Register of Controlled Trials, and Scopus. Primary outcomes were preservation of horizontal and vertical alveolar dimension and new bone formation inside the socket. Both pairwise and network meta-analysis (NMA) were undertaken to obtain estimates for primary outcomes. For NMA, prediction intervals were calculated to estimate clinical efficacy, and SUCRA was used to rank the materials based on their performance; multidimensional ranking was used to rank treatments based on dissimilarity. The manuscript represents the proceedings of a consensus conference of the Italian Society of Osseointegration (IAO). Results Twelve trials were included in the qualitative and quantitative analysis: 312 sites were evaluated. Autologous soft tissue grafts were associated with better horizontal changes compared to resorbable membranes. A statistically significant difference in favor of resorbable membranes, when compared to no membrane, was found, with no statistically significant heterogeneity. For the comparison between crosslinked and non-crosslinked membranes, a statistically significant difference was found in favor of the latter and confirmed by histomorphometric NMA analysis. Given the relatively high heterogeneity detected in terms of treatment approaches, materials, and outcome assessment, the findings of the NMA must be interpreted cautiously. Conclusions Coverage of the healing site is associated with superior results compared to no coverage, but no specific sealing technique and/or biomaterial provides better results than others. RCTs with larger sample sizes are needed to better elucidate the trends emerged from the present analysis. Clinical relevance Autologous soft tissue grafts and membranes covering graft materials in post-extraction sites were proved to allow lower hard tissue shrinkage compared to the absence of coverage material with sealing effect. Histomorphometric analyses showed that non-crosslinked membranes provide improved hard tissue regeneration when compared to crosslinked ones.

This study aimed to investigate the effectiveness of neoadjuvant chemotherapy in patients with breast cancer in different age groups and evaluate the impact of age group on survival outcome according to different treatment responses. Data were retrospectively collected from the cancer registry database of Kaohsiung Medical University Hospital in Taiwan under an approved protocol. Overall, 96 elder patients (aged >50 years) and 96 younger controls (aged ≤50 years) who received neoadjuvant chemotherapy and breast surgical treatment were examined after 1:1 matching. Logistic regression analysis was used to investigate the effectiveness of treatment response in patients of different age groups. Additionally, the Kaplan-Meier estimator and log-rank test were performed to evaluate the effect of age group and treatment response on disease-free and overall survival (OS). Although no direct significant association was found between age group and treatment response, several significant results were found in treatment response stratification analysis. Among 16 pathological complete response (pCR) patients, elder patients showed significantly greater 5-year disease-free survival (DFS) than younger patients (DFS rate, 85.7% vs. 0%, p = 0.041). However, in 176 non-pCR patients, elder patients showed poor DFS compared to younger patients (DFS rate, 16.6% vs. 32.3%; log-rank test, p = 0.031). With limited sample size and study design, our study results demonstrate that patients aged >50 years who achieved pCR after neoadjuvant chemotherapy could obtain better survival outcome than younger patients. However, the younger patients showed no survival benefits regardless of pCR status.

Context Observational associations between maternal polycystic ovary syndrome (PCOS) and offspring birth weight (BW) have been inconsistent and the causal relationship is still uncertain. Objective We conducted a 2-sample Mendelian randomization (MR) study to estimate the causal effect of maternal PCOS on offspring BW. Methods We constructed genetic instruments for PCOS with 14 single nucleotide polymorphisms (SNPs) which were identified in a genome-wide association study (GWAS) meta-analysis including 10 074 PCOS cases and 103 164 controls of European ancestry from 7 cohorts. The genetic associations of these SNPs with the offspring BW were extracted from summary statistics estimated by the Early Growth Genetics consortium (n = 406 063 European ancestry individuals) using the weighted linear model, an approximation method of structural equation model, which separated maternal genetic effects from fetal genetic effects. We used a 2-sample MR design to examine the causal relationship between maternal PCOS and offspring BW. Sensitivity analyses were conducted to assess the robustness of the MR results. Results We found little evidence for a causal effect of maternal PCOS on offspring BW (–6.1 g, 95% CI –16.8 g, 4.6 g). Broadly consistent results were found in the sensitivity analyses. Conclusion Despite the large scale of this study, our results suggested little causal effect of maternal PCOS on offspring BW. MR studies with a larger sample size of women with PCOS or more genetic instruments that would increase the variation of PCOS explained are needed in the future.

In order to evaluate the predictive effect of the controlled nutritional status (CONUT) score on the prognosis of patients with renal cell carcinoma (RCC) and upper urinary tract urothelial carcinoma (UTUC), a meta-analysis was performed. This systematic review has been registered on PROSPERO, the registration ID is CRD42021251879. A systematic search of the published literature using PubMed, Web of Science, Cochrane Library, EMBASE, and MEDLINE was performed. The fields of "renal cell cancer," "upper tract urothelial cancer," and "controlling nutritional status" and other fields were used as search terms. STATA 16 software was used to carry out data merging and statistical analysis of binary variables, Q test and χ2 tests were used to verify the heterogeneity between the included works of studies. Subgroup analysis and sensitivity analysis were used to explain the sources of heterogeneity between studies. Begg's test was used to assess publication bias between studies. From the first 542 studies retrieved, through strict inclusion and exclusion criteria, 7 studies finally met the requirements and were included in the meta-analysis. Pooled results indicated that high CONUT indicates worse over survival (OS) [HR = 1.70, 95% CI (1.43-2.03), P = 0.02], cancer-specific survival (CSS) [HR = 1.84, 95% CI (1.52-2.23), P = 0.01], recurrence-free survival (RFS) [HR = 1.60, 95% CI (1.26-2.03), P = 0.116], and disease-free survival (DFS) [HR = 1.47, 95% CI (1.20-1.81), P = 0.03]. Based on cancer type, cutoff value, region, and sample size, a subgroup analysis was performed. The results showed that OS and CSS were not affected by the above factors, and the high CONUT score before surgery predicted worse OS and CSS. In conclusion, this meta-analysis revealed that the preoperative CONUT score is a potential independent predictor of the postoperative prognosis of RCC/UTUC patients. A high CONUT predicts worse OS/CSS/DFS and RFS in patients.

PurposeThis study examines the impact of college education on incorporated and unincorporated self-employments. It specifically compares the effects on African Americans and Hispanics with the effects on Whites.Design/methodology/approachThe study sample was drawn from the US Current Population Survey between 1989 and 2018. Based on a sample size of 1,657,043 individuals, this study employed logit regression models to test the hypotheses. Racial variations were examined using African Americans and Hispanics as moderators.FindingsThe results suggest that college education increases incorporated self-employment and reduces unincorporated self-employment. The impact of college education on incorporated self-employment is stronger for African Americans and Hispanics than for Whites. In contrast, its effect on unincorporated self-employment is stronger for Whites than for African Americans and Hispanics.Research limitations/implicationsThe findings provide empirical evidence of how college experience changes the motivation of starting an incorporated or unincorporated business. The results suggest that college education impacts African Americans and Hispanics differently than Whites in pursuing their career path of entrepreneurship.Originality/valueIt is the first study that examines the relationship between college education and incorporated/unincorporated self-employment. It also sheds light on radical variations.

We introduce a simulation method for dynamic portfolio valuation and risk management building on machine learning with kernels. We learn the dynamic value process of a portfolio from a finite sample of its cumulative cash flow. The learned value process is given in closed form thanks to a suitable choice of the kernel. We show asymptotic consistency and derive finite sample error bounds under conditions that are suitable for finance applications. Numerical experiments show good results in large dimensions for a moderate training sample size.

The purpose of this study was to compare the application of the print module and the electronic module to see the indicators of the character of social care. This type of research is quantitative research. This study involved two variables, namely learning teaching materials in class with a sample size of 47 students. Data analysis used descriptive and inferential statistics. The character of students' social care can be seen in the application of the electronic module and the print module. The result, from the two teaching materials, the social care character of SD 64/I Muara Bulian students was dominant in the good category, while the social care character of students with the application of the dominant print module was sufficient.

Of 25% of randomised controlled trials (RCTs) on interventions for inflammatory bowel disease (IBD) have no power calculation. To systematically review RCTs reporting interventions for the management of IBD and to produce data for minimum sample sizes that would achieve appropriate power using the actual clinical data. We included RCTs retrieved from Cochrane IBD specialised Trial register and CENTRAL investigating any form of therapy for either induction or maintenance of remission against control, placebo, or no intervention of IBD in patients of any age. The relevant data was extracted, and the studies were grouped according to the intervention used. We recalculated sample size and the achieved difference, as well as minimum sample sizes needed in the future. A total of 105 trials were included. There was a large discrepancy between the estimated figure for the minimal clinically important difference used for the calculations (15% group differences observed 30% used for calculation) explaining substantial actual sample size deficits. The minimum sample sizes indicated for future trials based on the 25 years of trial data were calculated and grouped by the intervention. A third of intervention studies in IBD within the last 25 years are underpowered, with large variations in the calculation of sample sizes. The authors present a sample size estimate resource constructed on the published evidence base for future researchers and key stakeholders within the IBD trial field. [Abstract copyright: ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.]

In this study we propose a sequential test for hypothesis testing on the $$C_{pmk}$$ process capability index. Furthermore, we propose a sequential sampling plan for lot acceptance based on $$C_{pmk}$$ . We compare the statistical properties of the sequential procedures with the performance of the corresponding non-sequential methodologies by carrying out an extensive simulation study. The results show that the proposed sequential methods make it possible to reach decisions much more quickly, on average, than the fixed sample size procedures with the same discriminating power.

Patient-centred outcomes are increasingly recognised as crucial measures of healthcare quality. Days alive and at home up to 30 days after surgery (DAH30 ) is a validated and readily obtainable patient-centred outcome measure that integrates much of the peri-operative patient journey. However, the minimal difference in DAH30 that is clinically important to patients is unknown. We designed and administered a 28-item survey to evaluate the minimal clinically important difference in DAH30 among adult patients undergoing inpatient surgery. Patients were approached pre-operatively or within 2 days postoperatively. We did not study patients undergoing day surgery or nursing home residents. Patients ranked their opinions on the importance of discharge home using a Likert scale (from 1, not important at all to 6, extremely important) and the minimum number of extra days at home that would be meaningful using this scale. We recruited 104 patients; the survey was administered pre-operatively to 45 patients and postoperatively to 59 patients. The mean (SD) age was 53.5 (16.5) years, and 51 (49%) patients were male. Patients underwent a broad range of surgery of mainly intermediate (55%) to major (33%) severity. The median minimal clinically important difference for DAH30 was 3 days; this was consistent across a broad range of scenarios, including earlier discharge home, complications delaying hospital discharge and the requirement for admission to a rehabilitation unit. Discharge home earlier than anticipated and discharge home rather than to a rehabilitation facility were both rated as important (median score = 5). Empirical data on the minimal clinically important difference for DAH30 may be useful to determine sample size and to guide the non-inferiority margin for future clinical trials.

In this paper an easy to implement method of stochastically weighing short and long-memory linear processes is introduced. The method renders asymptotically exact size confidence intervals for the population mean which are significantly more accurate than their classic counterparts for each fixed sample size n. It is illustrated both theoretically and numerically that the randomization framework of this paper produces randomized (asymptotic) pivotal quantities, for the mean, which admit central limit theorems with smaller magnitudes of error as compared to those of their leading classic counterparts. An Edgeworth expansion result for randomly weighted linear processes whose innovations do not necessarily satisfy the Cramer condition, is established. Numerical illustrations and applications to real world data are also included.

Aims: To determine the relationship between distant learning and neck pain during COVID-19 pandemic especially among medical students, thus we aim to assess prevalence of neck pain for specific Group and time. Study Design: An observational cross-sectional study. Place and Duration of Study: Conducted in Saudi Arabia, between July 2020and October 2021. Methodology: This is a cross-sectional observational descriptive study that started in July 2020. Our target population include all medical students either male or female suffering from neck pain in Kingdom of Saudi Arabia during the period of distant learning due to the Covid-19 pandemic. Sample size: Total Number of medical students in KSA (26126), Confidence level 95% and margin of error 5%. The sample size 379 was estimated using the Qualtrics calculator. Results: A total of 2071 participants were a part of study. Most of them are female n=1509(72.9%) and least of them are male n=562(27.1%). The minimum age of participant was 18 years old n=61(2.9%), And the maximum age was 30 years old n=10(0.5%). Most of medical students noticed increase of neck pain during the period of pandemic. Most of them had noticed exacerbation of neck pain during COVID-19 pandemic n=1002(72.3%), where n=384(27.7%) had same pain before and during pandemic. Majority of them were completely relying on electronic devices for their education. Conclusion:A high Pervasiveness of neck pain in the medical students during COVID-19 pandemic has been observed. Most of medical students noticed increase of neck pain during the period of pandemic. Majority of them were completely relying on electronic devices for their education.

Summary We consider the problem of testing for the presence of linear relationships between large sets of random variables based on a postselection inference approach to canonical correlation analysis. The challenge is to adjust for the selection of subsets of variables having linear combinations with maximal sample correlation. To this end, we construct a stabilized one-step estimator of the Euclidean norm of the canonical correlations maximized over subsets of variables of prespecified cardinality. This estimator is shown to be consistent for its target parameter and asymptotically normal, provided the dimensions of the variables do not grow too quickly with sample size. We also develop a greedy search algorithm to accurately compute the estimator, leading to a computationally tractable omnibus test for the global null hypothesis that there are no linear relationships between any subsets of variables having the prespecified cardinality. We further develop a confidence interval that takes the variable selection into account.

Purpose: We assessed the extent to which language, speech, and fine/gross motor skills in preschoolers with developmental language disorder (DLD; also referred to as specific language impairment) predicted language outcome two years later.Method: Participants with DLD (n = 15) and typical development (TD; n = 14) completed language, speech, and fine/gross motor assessments annually, beginning as 4- to 5-year-olds (Year 1 timepoint) and continuing through 6 to 7 years of age (Year 3 timepoint). We performed Pearson correlation and hierarchical regression analyses to examine the relative contributions of Year 1 language, speech, and motor skills to Year 3 language outcome in each group.Result: Among children with DLD, Year 1 fine/gross motor scores positively correlated with Year 3 language scores, uniquely explaining 40% of the variance in language outcomes. Neither Year 1 language, speech-sound, nor speech-motor scores predicted language outcome in this group. Among children with TD, only Year 1 language predicted language outcome.Conclusion: This small longitudinal study reveals that, among preschoolers with DLD, certain early fine/gross motor deficits predict persistent language impairment. Future research that includes larger sample sizes and motor tasks that incorporate complex sequencing will enhance the understanding of the relationship between language, speech, and motor skills; specifically, whether certain motor deficits simply co-occur with language deficits or whether they are tied to DLD through shared impairments in sequential learning mechanisms.

Background. Pregnancy leads to several skin changes, but evidence about structural and functional skin changes is scarce. Findings on skin structure and function in children in their first year reveal rapid skin maturation, but evidence indicates that in particular, water holding and transport mechanisms are different from adults. Important questions include whether maternal cutaneous properties predict infant skin condition, and if so, how. This is especially relevant for the skin’s microbiome because it closely interacts with the host and is assumed to play a role in many skin diseases. Therefore, the study objective is to explore characteristics of skin and hair of pregnant women and their newborns during pregnancy and in the first six months after delivery and their associations. Methods. The study has an observational longitudinal design. We are recruiting pregnant females between 18 and 45 years using advertisement campaigns in waiting areas of gynecologists and hospital’s outpatient services. A final sample size of n = 100 women is the target. We perform noninvasive, standardized skin, hair, and skin microbiome measurements. We establish the baseline visit during pregnancy until at the latest four weeks before delivery. We schedule follow-up visits four weeks and six months after birth for mothers and their newborns. We will calculate descriptive statistical methods using frequencies and associations over time depending on scale levels of the measurements. Discussion. The majority of previous studies that have investigated infants’ skin microbiome and its associations used cross-sectional designs and focused on selected characteristics in small samples. In our longitudinal study, we will characterize a broad range of individual and environmental characteristics of mothers and their newborns to evaluate interrelationships with skin parameters and their changes over time. Considering the combination of these multiple variables and levels will allow for a deeper understanding of the complex interrelationship of the newborn’s skin maturation. This trial is registered with ClinicalTrials.gov (Identifier: NCT04759924).

Small area estimation (SAE) methods can provide information that conventional direct survey estimation methods cannot. The use of small area estimates based on linear and generalized linear mixed models is still very limited, possibly because of the perceived complexity of estimating the root mean square errors (RMSEs) of the estimates. This paper outlines a study used to determine the conditions under which the estimated RMSEs, produced as part of statistical output (‘plug-in’ estimates of RMSEs) could be considered appropriate for a practical application of SAE methods where one of the main requirements was to use SAS software. We first show that the estimated RMSEs created using an EBLUP model in SAS and those obtained using a parametric bootstrap are similar to the published estimated RMSEs for the corn data in the seminal paper by Battese, Harter and Fuller. We then compare plug-in estimates of RMSEs from SAS procedures used to create EBLUP and EBP estimators against estimates of RMSEs obtained from a parametric bootstrap. For this comparison we created estimates of current smoking in males for 153 local government areas (LGAs) using data from the NSW Population Health Survey in Australia. Demographic variables from the survey data were included as covariates, with LGA-level population proportions, obtained mainly from the Australian Census used for prediction. For the EBLUP, the estimated plug-in estimates of RMSEs can be used, provided the sample size for the small area is more than seven. For the EBP, the plug-in estimates of RMSEs are suitable for all in-sample areas, out-of-sample areas need to use estimated RMSEs that use the parametric bootstrap.

Background: Athletes of all sports often have shoulder instability, most commonly as anterior shoulder instability (ASI). For overhead athletes (OHAs) and those participating in throwing sports, clinical and surgical decision making can be difficult owing to a lack of long-term outcome studies in this population of athletes. Purpose/Hypothesis: To report presentation characteristics, pathology, treatment strategies, and outcomes of ASI in OHAs and throwers in a geographic cohort. We hypothesized that OHAs and throwers would have similar presenting characteristics, management strategies, and clinical outcomes but lower rates of return to play (RTP) when compared with non-OHAs (NOHAs) and nonthrowers, respectively. Study Design: Cohort study; Level of evidence, 3. Methods: An established geographic medical record system was used to identify OHAs diagnosed with ASI in the dominant shoulder. An overall 57 OHAs with ASI were matched 1:2 with 114 NOHAs with ASI. Of the OHAs, 40 were throwers. Sports considered overhead were volleyball, swimming, racquet sports, baseball, and softball, while baseball and softball composed the thrower subgroup. Records were reviewed for patient characteristics, type of sport, imaging findings, treatment strategies, and surgical details. Patients were contacted to collect Western Ontario Shoulder Instability index (WOSI) scores and RTP data. Statistical analysis compared throwers with nonthrowers and OHAs with NOHAs. Results: Four patients, 3 NOHAs and 1 thrower, were lost to follow-up at 6 months. Clinical follow-up for the remaining 167 patients (98%) was 11.9 ± 7.2 years (mean ± SD). Of the 171 patients included, an overall 41 (36%) NOHAs, 29 (51%) OHAs, and 22 (55%) throwers were able to be contacted for WOSI scores and RTP data. OHAs were more likely to initially present with subluxations (56%; P = .030). NOHAs were more likely to have dislocations (80%; P = .018). The number of instability events at presentation was similar. OHAs were more likely to undergo initial operative management. Differences in rates of recurrent instability were not significant after initial nonoperative management (NOHAs, 37.1% vs OHAs, 28.6% [ P = .331] and throwers, 21.2% [ P = .094]) and surgery (NOHAs, 20.5% vs OHAs, 13.0% [ P = .516] and throwers, 9.1% [ P = .662]). Rates of revision surgery were similar (NOHAs, 18.0% vs OHAs, 8.7% [ P = .464] and throwers, 18.2% [ P > .999]). RTP rates were 80.5% in NOHAs, as compared with 71.4% in OHAs ( P = .381) and 63.6% in throwers ( P = .143). Median WOSI scores were 40 for NOHAs, as compared with 28 in OHAs ( P = .425) and 28 in throwers ( P = .615). Conclusion: In a 1:2 matched comparison of general population athletes, throwers and OHAs were more likely to have more subtle instability, as evidenced by higher rates of subluxations rather than frank dislocations, when compared with NOHAs. Despite differences in presentation and the unique sport demands of OHAs, rates of recurrent instability and revision surgery were similar across groups. Similar outcomes in terms of RTP, level of RTP, and WOSI scores were achieved for OHAs and NOHAs, but these results must be interpreted with caution given the limited sample size.

The ongoing COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in significant death and morbidity rates around the globe. SARS-CoV-2 infection has been linked to 43.3 million confirmed cases worldwide, killing 1.15 million people. Physical separation, quarantine, and isolation were successful in minimizing the number of individuals who became sick during the epidemic, but the lack of immunity in the community makes them vulnerable to further waves of SARS-CoV-2 infection. Elderly persons (those 60 and older) and those with pre-existing medical problems are particularly vulnerable. Material and Methods: In this observation study, people who were vaccinated with sinopharm vaccine and sinovac vaccine were included to see the response of vaccine in the body. The aim of the study was to compare the rise in the antibody level after 2 doses of two different COVID-19 vaccines i.e sinopharm and sinovac. Initially, in this pilot study, 40 people were included randomly from our health care team, after proper informed consent regarding the study. Results: Among total 40 people were involved, male were 21 of 40 (52.5%) and female were 19 of 40 (47.5%). Most of the individuals were doctors (26 of 40, 65%). Mean age, weight, height and body mass index (BMI) are also shown below. Conclusion: This study was to report the response of people of Pakistan toward sinopharm and sinoVac vaccines in terms of COVID antibody level. Response of the body was around 40 to 50% for sinopharm and 50 to 70 percent towards CoronaVac vaccine. Further data collection is being done to improve sample size and better outcome.

The stepped wedge cluster randomized trial (SW-CRT) is an increasingly popular design for evaluating health service delivery or policy interventions. An essential consideration of this design is the need to account for both within-period and between-period correlations in sample size calculations. Especially when embedded in health care delivery systems, many SW-CRTs may have subclusters nested in clusters, within which outcomes are collected longitudinally. However, existing sample size methods that account for between-period correlations have not allowed for multiple levels of clustering. We present computationally efficient sample size procedures that properly differentiate within-period and between-period intracluster correlation coefficients in SW-CRTs in the presence of subclusters. We introduce an extended block exchangeable correlation matrix to characterize the complex dependencies of outcomes within clusters. For Gaussian outcomes, we derive a closed-form sample size expression that depends on the correlation structure only through two eigenvalues of the extended block exchangeable correlation structure. For non-Gaussian outcomes, we present a generic sample size algorithm based on linearization and elucidate simplifications under canonical link functions. For example, we show that the approximate sample size formula under a logistic linear mixed model depends on three eigenvalues of the extended block exchangeable correlation matrix. We provide an extension to accommodate unequal cluster sizes and validate the proposed methods via simulations. Finally, we illustrate our methods in two real SW-CRTs with subclusters.

Hospitals, which play an important role in reducing injuries and casualties, must be prepared for a crowd of people in emergencies. The present study aimed to survey and collect data on the likely behaviours of people under emergency circumstances in hospitals in order to improve emergency response plans in these places. The target population was all individuals present in three hospitals from Tabriz (including patients, companions and treatment staff), and the sample size was 1145. A questionnaire was administered to this population in order to collect the data. The comparison of different groups was performed based on participants' gender and their role. Results showed that, in general, everyone in the surveyed hospitals is more likely to choose a reactive strategy rather than a preventive strategy as well as a cooperative strategy rather than a competitive strategy, and less willing to use lifts during emergencies. Comparing different strategies utilized by different people resulting from ordered logit models revealed that there are significant differences in evacuation strategies between men and women as well as between treatment staff and all respondents. Men were more likely to select a proactive strategy rather than a reactive strategy compared to women. Also, the treatment staff group were more likely to employ a cooperative strategy and less likely to use a competitive strategy compared to other people. In view of the role of hospitals, the results of this study can play a major role in policy-making to predict the behaviour of different individuals in healthcare settings and perform needs assessment to consider the necessary facilities or raining required for different people in various countries.

A random delayed treatment effect is expected in a confirmatory clinical trial for an immunotherapy due to the individual heterogeneity of physiological conditions. For this reason, the delay time will be assumed to follow a continuous distribution that is difficult to estimate accurately based on the early-phase data, which hinders the specification of the most powerful weighted log-rank test. Therefore, we propose a simulation-based maximum duration design with a robustly powerful Maxcombo test for a group sequential trial for the immunotherapy with the random delayed treatment effect. The design obtains the group sequential boundaries by a simulation procedure and determines the required maximum sample size using a one-dimensional search in which another simulation procedure is used to calculate empirical power. The simulation researches proved the accuracy of the group sequential boundaries and their robustness against the misspecified maximum sample sizes for large samples and revealed their moderate sensitivity against the misspecified survival distributions under the null hypothesis of no difference. The studies investigated whether the type I error rate would inflate under the "inferior" null hypothesis and evaluated the robustness against different distributions of the delay time in terms of the empirical power among the Maxcombo tests and component weighted log-rank tests.

Objective. Delirium is a temporary neuropsychiatric syndrome characterized by fluctuations in cognition and attention. Delirium is one of the most common complications seen in old individuals after orthopaedic surgery. With a high incidence, the clinical picture of delirium increases the length of hospital stay and increases healthcare-related costs. This study has aimed to systematically review the national and international studies that investigated the risk factors leading to delirium in geriatric patients after orthopaedic surgery and to perform a meta-analysis using the data reported by those studies. Materials and Methods. A preliminary literature review was performed on six databases. The following English keyword combinations were used including 'Orthopaedic Surgery', 'Geriatrics', 'Elderly', and 'Delirium'. The results of trials were evaluated with random or fixed effect model according to the heterogeneity. Statistical evaluation was performed by using Comprehensive Meta Analysis version 3 programme. Results. The total sample size of the studies included in the analysis was 892. In geriatric patients; who had undergone orthopaedic surgery and developed delirium, the random-effects model revealed a high-level, in the positive direction, and statistically significant (p

A recently proposed SLOPE estimator (arXiv:1407.3824) has been shown to adaptively achieve the minimax $\ell_2$ estimation rate under high-dimensional sparse linear regression models (arXiv:1503.08393). Such minimax optimality holds in the regime where the sparsity level $k$, sample size $n$, and dimension $p$ satisfy $k/p \rightarrow 0$, $k\log p/n \rightarrow 0$. In this paper, we characterize the estimation error of SLOPE under the complementary regime where both $k$ and $n$ scale linearly with $p$, and provide new insights into the performance of SLOPE estimators. We first derive a concentration inequality for the finite sample mean square error (MSE) of SLOPE. The quantity that MSE concentrates around takes a complicated and implicit form. With delicate analysis of the quantity, we prove that among all SLOPE estimators, LASSO is optimal for estimating $k$-sparse parameter vectors that do not have tied non-zero components in the low noise scenario. On the other hand, in the large noise scenario, the family of SLOPE estimators are sub-optimal compared with bridge regression such as the Ridge estimator., 50 pages, 18 figures

Introduction: Child maltreatment and neglect are considered important issues in the US. However, parental-child violence is not studied enough to provide a comprehensive understanding of the underlying causes. Aim: To determine the parent's reported causes of actual children who are abusing the age bracket of 6 to 12 years. Methods and Materials: The descriptive survey study design was used with a quantitative research approach conducted in a selected community area of Wardha town. The sample size was 200 parents with children aged 6 to 12. Pre-tested and validated structured questionnaires were used. The data gathered was registered into the Microsoft Excel sheet. The statistical analysis ended up being done SPSS. The frequencies and percentages of categorical variables had been provided. Results: The parents reported causes for physical abuse among children of 6 to 12 years were seen into 4 categories, once in a week, sometimes, twice in a week, and never respectively. 37.5% of the parents reported twice in a week and 62.5% of them never reported causes. The mean score of parents who reported causes of physically abuse children in the age group of 6 to 12 years was 44.58 ± 4.66 and the range of the score was 32 to 56. Demographic variables such as age in years, gender, monthly income, education, area of residence, and relationship with parents were statistically associated with their reported causes. Conclusion: Community-based methods, such as house visits, are incredibly efficient in changing the behavior of parents at risk of misuse. Targeted programs for moms with mental disorders and substance abuse are also shown to be effective in stopping emotional abuse [1].

Existing procedures for testing measurement invariance focus mainly on group-level comparisons rather than individual comparisons (i.e., the main conclusion typically concerns the question of comparability of group means). We propose a set of intuitive graphical displays called Person-Level Assessment of Measurement Invariance (PLAMI), which attempt to provide information about the effect of the lack of measurement invariance on the level of person scores. This information complements the group-level information contained in model fit indices and overall effect size indices, and should be especially useful for practitioners using tests for individual diagnostics. PLAMI uses results from the multiple-group factor analysis to estimate and visualize score distortions in terms of expected score difference between members of different groups and the probability of an unacceptably high score difference, conditional for the value of latent trait. The stability of the results can be evaluated by means of resampling. Simulation can be used for an a priori evaluation of the sample size adequacy. We illustrate the proposed plots on two real examples involving testing measurement invariance of the Machiavellianism scale, and we demonstrate the added value of PLAMI compared to the use of fit indices alone.

The study aimed at assessing the effects of sports gambling among the youths of Blantyre City in Southern Malawi. In this study, the sample size was made up of 30 youths compromising 19 males and 11 females. They were randomly selected by the researcher through probability sampling. Questionnaires were used to collect data for the study. The study achieved a 100% response rate. The study revealed that 84.2% of the youths involved in sports betting are not aware of any of the rules or regulations protecting them as bettors, 68% of them do not invest in the money they get. Asked how this activity has affected them either negatively or positively, it is discovered it has brought more harm than good. A total of 9 of the respondents were affected by addiction, 5 of the respondents had financial constraints caused by betting, 3 of the respondents agreed that it wasted their time and 8 of them said that it affected them positively as it helps them spend their leisure time. The study established that sports betting is an activity that can jeopardize the social and moral welfare of the youths; hence, more research on sports betting addiction is needed about the youths to examine more the effects associated with this activity in Blantyre; and that more protection must be devised for the youths through the main stakeholders to safeguard their moral, social and academic welfare. The government policy should be more strengthened and tightened by increasing the eligible age for bettors and that more awareness about pathological betting is needed among the youths of Blantyre. Key words: Gambling, betting, youths, effect, sports.

Randomized controlled trials (RCTs) are the most robust study design for evaluating the safety and efficacy of a therapeutic intervention. However, their internal validity are at risk when evaluating surgical interventions. This review summarizes existing expertise- based trials in surgery and related methodological concepts to guide surgeons performing this work. We provide caseloads required to reach the learning curve for various surgical interventions and report criteria for expertise from published and unpublished expertise-based trials. In addition, we review design and implementation concepts of expertise-based trials, including recruitment of surgeons, crossover, ethics, generalizability, sample size and definitions for learning curve. Several RCTs have used an expertise-based design. We found that the majority of definitions used for expertise were vague, heterogeneous, and inconsistent across trials evaluating the same surgical intervention. Statistical methods exist to adjust for the learning curve; however, there is limited guidance. We developed the following criteria for surgical expertise for future trials: 1) decide on the proxy to be used for the learning curve, and 2) assess eligible surgeons by comparing their performance to the previously defined expertise criteria.

Our empirical analysis is based on Statistics Canada’s worker-firm matched data set, the 2003 Workplace and Employee Survey (WES). The sample size is substantial: about 4,000 workers over the age of 50 and 12,000 between the ages of 25 and 49. Training was a focus of the survey, which offers a wealth of worker-related and firm-related training variables.We found that the mean probability of receiving training was 9.3 percentage points higher for younger workers than for older ones. Almost half of the gap is explained by older workers having fewer training-associated characteristics (personal, employment, workplace, human resource practices and occupation/industry/region), and slightly more than half by them having a lower propensity to receive training, this being the gap that remained after we controlled for differences in training-associated characteristics. Their lower propensity to receive training likely reflects the higher opportunity cost of lost wages during the time spent in training, possible higher psychological costs and lower expected benefits due to their shorter remaining work-life and lower productivity gains from training, as discussed in the literature.The lower propensity of older workers to receive training tended to prevail across 54 different training measures, with notable exceptions discussed in detail. We found that older workers can be trained, but their training should be redesigned in several ways: by making instruction slower and self-paced; by assigning hands-on practical exercises; by providing modular training components to be taken in stages; by familiarizing the trainees with new equipment; and by minimizing required reading and amount of material covered. The concept of “one-size-fits- all” does not apply to the design and implementation of training programs for older workers., Notre analyse empirique est fondée sur l’ensemble des données appariées entre les travailleurs et les entreprises de Statistique Canada, le Workplace and Employee Survey (WES) de 2003. La taille de l’échantillon est importante, environ 4 000 travailleurs de plus de 50 ans et 12 000 qui ont entre 25 et 49 ans. Cette enquête est centrée sur la formation, de sorte qu’elle comporte une multitude de variables sur ce sujet tant pour les travailleurs que pour les entreprises.Notre analyse économétrique a révélé que la probabilité moyenne de recevoir une formation était de 9,3 points de pourcentage plus élevée chez les jeunes que chez les travailleurs plus âgés. Près de la moitié de cet écart peut être attribué au fait que les travailleurs âgés ont moins de caractéristiques associées à la réception de la formation (c’est-à-dire caractéristiques personnelles, d’emploi, du milieu de travail, des pratiques en matière de ressources humaines et de la profession/industrie/région). D’autre part, un peu plus de la moitié de l’écart est attribué au fait qu’ils ont moins tendance à recevoir des formations après avoir pris en compte leurs caractéristiques. Cela reflète probablement un coût d’opportunité plus élevé des salaires perdus pendant la formation et des coûts psychiques possiblement plus élevés pour les travailleurs plus âgés. Comme le révèle la littérature, cela reflète aussi le fait qu’il y a moins d’avantages à former les personnes plus âgées en raison de leur horizon de vie professionnelle plus court et des gains de productivité plus faibles associés à la formation.La faible tendance des travailleurs âgés à recevoir une formation s’exprime dans 54 mesures de la formation, avec quelques exceptions notables. Nous constatons que les travailleurs âgés peuvent être formés, mais cela nécessite une formation conçue pour répondre aux besoins des travailleurs âgés. Ces caractéristiques comprennent une instruction plus lente et auto-rythmée, des exercices pratiques, des composants de formation modulaires qui se construisent par étapes, les familiariser avec de nouveaux équipements et minimiser la lecture requise et la quantité de matériel couvert. Le concept d’uniformité ne s’applique pas à la conception et à la mise en oeuvre de formations pour les travailleurs âgés.

Introduction Fetal alcohol spectrum disorders (FASD) are highly prevalent developmental disabilities associated with prenatal alcohol exposure. In addition to varied strengths and unique talents, people with FASD experience significant challenges, including in adaptive functioning. Adaptive functioning refers to skills related to everyday life such as communication, practical skills, and social skills. For the current review we aimed to understand how adaptive functioning in FASD compares to that of nonexposed individuals and those with attention deficit-hyperactivity disorder (ADHD). Additionally, we investigated how this relationship may change based on IQ, executive functioning, and age. Method The current review was registered in the International Prospective Register of Systematic Reviews (PROSPERO). Studies were eligible for inclusion if they measured adaptive functioning and included an FASD group and at least one eligible comparison group. Articles available in May 2021 in PubMed, PsycInfo, Scopus, and ProQuest Dissertations were searched. Publication bias was assessed using Egger's regression and three-level random effects models were computed for all domains of adaptive functioning. Possible moderation of IQ, executive functioning, and age were investigated if heterogeneity analyses were significant. A post-hoc moderation analysis of recruitment method was also completed. Results Thirty studies were included. Individuals with FASD had significantly lower adaptive functioning relative to other groups, with effect sizes ranging from 1.04-1.35 compared to nonexposed groups and .30-.43 compared to ADHD groups. No significant moderating effects were found for IQ, or age; executive functioning significantly moderated communication skills in FASD compared to the nonexposed group. Recruitment method significantly affected this relationship, with larger effect sizes on average found for clinically-identified samples compared to at-risk or population samples. Conclusions Individuals with FASD have impairments in adaptive functioning relative to nonexposed and ADHD groups, regardless of IQ, executive functioning, or age. Limitations include low sample sizes in some comparisons and limited age range.

Importance SARS-CoV-2 has infected over 200 million people worldwide, resulting in more than 4 million deaths. Randomized controlled trials are the single best tool to identify effective treatments against this novel pathogen. Objective To describe the characteristics of randomized controlled trials of treatments for COVID-19 in the United States launched in the first 9 months of the pandemic. Design, Setting, and Participants We conducted a cross-sectional study of all completed or actively enrolling randomized, interventional, clinical trials for the treatment of COVID-19 in the United States registered on www.clinicaltrials.gov as of August 10, 2020. We excluded trials of vaccines and other interventions intended to prevent COVID-19. Main Outcomes and Measures We used descriptive statistics to characterize the clinical trials and the statistical power for the available studies. For the late-phase trials (i.e., phase 3 and 2/3 studies), we compared the geographic distribution of the clinical trials with the geographic distribution of people diagnosed with COVID-19. Results We identified 200 randomized controlled trials of treatments for people with COVID-19. Across all trials, 87 (43.5%) were single-center, 64 (32.0%) were unblinded, and 80 (40.0%) were sponsored by industry. The most common treatments included monoclonal antibodies (N=46 trials), small molecule immunomodulators (N=28), antiviral medications (N=24 trials), and hydroxychloroquine (N=20 trials). Of the 9 trials completed by August 2020, the median sample size was 450 (IQR 67–1113); of the 191 ongoing trials, the median planned sample size was 150 (IQR 60–400). Of the late-phase trials (N=54), the most common primary outcome was a severity scale (N=23, 42.6%), followed by a composite of mortality and ventilation (N=10, 18.5%), and mortality alone (N=6, 11.1%). Among these late-phase trials, all trials of antivirals, monoclonal antibodies, or chloroquine/hydroxychloroquine had a power of less than 25% to detect a 20% relative risk reduction in mortality. Had the individual trials for a given class of treatments instead formed a single trial, the power to detect that same reduction in mortality would have been greater than 98%. There was large variability in access to trials with the highest number of trials per capita in the Northeast and the lowest in the Midwest. Conclusions and Relevance A large number of randomized trials were launched early in the pandemic to evaluate treatments for COVID-19. However, many trials were underpowered for important clinical endpoints and substantial geographic disparities were observed, highlighting the importance of improving national clinical trial infrastructure. Supplementary Information The online version contains supplementary material available at 10.1007/s11606-021-07167-9.

Definitive clinical trials are resource intensive, often requiring a large number of participants over several years. One approach to improving the efficiency of clinical trials is to incorporate historical information into the primary trial analysis. This approach has tremendous potential in the areas of pediatric or rare disease trials, where achieving reasonable power is difficult. In this manuscript, we introduce a novel Bayesian group-sequential trial design based on Multisource Exchangeability Models, which allows for dynamic borrowing of historical information at the interim analyses. Our approach achieves synergy between group sequential and adaptive borrowing methodology to attain improved power and reduced sample size. We explore the frequentist operating characteristics of our design through simulation and compare our method to a traditional group-sequential design. Our method achieves earlier stopping of the primary study while increasing power under the alternative hypothesis but has a potential for type I error inflation under some null scenarios. We discuss the issues of decision boundary determination, power and sample size calculations, and the issue of information accrual. We present our method for a continuous and binary outcome, as well as in a linear regression setting.

Estimation of the dose-response curve for efficacy and subsequent selection of an appropriate dose in phase II trials are important processes in drug development. Various methods have been investigated to estimate dose-response curves. Generally, these methods are used with equal allocation of subjects for simplicity; nevertheless, they may not fully optimize performance metrics because of nonoptimal allocation. Optimal allocation methods, which include adaptive allocation methods, have been proposed to overcome the limitations of equal allocation. However, they rely on asymptotics, and thus sometimes cannot efficiently optimize the performance metric with the sample size in an actual clinical trial. The purpose of this study is to construct an adaptive allocation rule that directly optimizes a performance metric, such as power, accuracy of model selection, accuracy of the estimated target dose, or mean absolute error over the estimated dose-response curve. We demonstrate that deep reinforcement learning with an appropriately defined state and reward can be used to construct such an adaptive allocation rule. The simulation study shows that the proposed method can successfully improve the performance metric to be optimized when compared with the equal allocation, D-optimal, and TD-optimal methods. In particular, when the mean absolute error was set to the metric to be optimized, it is possible to construct a rule that is superior for many metrics.

This study used a meta-analysis to examine the relationship between authenticity and tourist loyalty. A total of 144 effect sizes and 27,986 accumulated sample sizes from 68 independent empirical s...

Background & aims A pre-emptive transjugular intrahepatic portosystemic shunt (p-TIPSS) after acute variceal bleeding (AVB) is advocated. However, when compared with the current standard of care (SOC), the survival benefit of p-TIPSS is questionable. We performed a systematic review, meta-analysis and trial sequential analysis of randomised control trials (RCT) to assess the survival benefit of p-TIPSS in patients with cirrhosis and AVB. Methods Comprehensive literature search of 3 bibliographic databases (MEDLINE, EMBASE, Cochrane) was conducted from inception till May2021. All study types evaluating the survival benefit of p-TIPSS in AVB were considered for inclusion. The relative risk (RR) of mortality and re-bleeding at 6-weeks and mortality at 1-year with a random effects model was computed. Trial sequential analysis (TSA) was performed for the primary outcome of 6-weeks mortality. Results A total of 9 studies(4 RCTs and 5 cohort) comprising 2861 patients with AVB were included. The overall pooled risks of mortality at 6-weeks and 1-year were 17.9%(95%CI:16.5-19.3%) and 26.7%(95%CI:25.0-28.3%) respectively. Although p-TIPSS was associated with lower 6-weeks rebleeding risk (RR=0.20;95%CI=0.13-0.29, I2 =0%), data from pooled RCTs showed no significant difference in mortality at 6-weeks (RR=0.33; 95% CI=0.08-1.36, I2 =63%) or at 1-year (RR=0.76;95%CI=0.51-1.14, I2 =30%). Using TSA, required sample size to detect a 20% relative risk reduction in mortality at 6-weeks with p-TIPSS was estimated to be 6317, which is beyond the total number of patients available for analysis. Conclusions This meta-analysis found that the available data from RCTs is insufficient to confer 6-weeks mortality benefit with p-TIPSS compared to SOC, thus adequately powered RCT's are required.

El presente estudio tuvo como objetivo evaluar la eficiencia estadística de seis estimadores de muestreo para plantear una estrategia de muestreo óptima en términos de precisión y tiempo que permita realizar inventarios maderables operativos que apoyen la toma de decisiones orientadas a mejorar el manejo técnico de plantaciones forestales comerciales de Tectona grandis (teca), establecidas en Campeche, México. Para ello, se evaluaron 8 830 sitios de muestreo ubicados en 2 207.5 hectáreas. Cada sitio rectangular de 72 m2 incluyó nueve cepas, se contabilizó el número de árboles vivos y se midió el diámetro normal. La altura total y volumen por árbol se estimaron con modelos tipo Chapman-Richards y Schumacher-Hall, respectivamente. El área basal y el volumen total por sitio se proyectó a nivel de hectárea. Se estratificó por clase de edad; el área basal y la edad de la plantación se utilizaron como variables auxiliares. La estrategia de muestreo para estimar el volumen medio se conformó al asociar como diseño de muestreo al muestreo simple al azar con el estimador de razón específica en muestreo estratificado, con una estratificación por clases de edad de un año y el área basal como variable auxiliar, esto dio la precisión de 0.21 %. El tamaño de muestra en el muestreo estratificado se redujo 68.3 %, con precisión de 2.5 % del muestreo original, lo cual implica que el esfuerzo de muestreo y el tiempo de ejecución para realizar el inventario operativo puede reducirse, con la consecuente disminución de los costos implícitos.

Background Face masks have been proven to be effective in protecting the public against airborne transmitted diseases when fitted appropriately. However, for homemade cloth masks and surgical masks, the fit is often poor, allowing viruses to escape through the gap. Objective This work aims to identify the correlation between the mask leakage, mask configurations, and individual’s facial features. Methods A novel locally morphing 3D face model, and a minimum-energy-based mask deployment model are used to systematically examine the mask fit for a large cohort of exemplars. Results The results show that the mask size and tuck-in ratio, along with selective facial features, especially nose height and chin length, are key factors determining the leakage location and extent. A polynomial regression model is presented for mask fitness based on localized facial features. Significance This study is a complete pipeline to test various masks on a wide range of faces with controlled modification of distinct regions of the face, which is difficult to achieve with human subjects, and provide knowledge on how the masks should be designed in the future. Impact statement The face mask “fit” affects the mask’s efficacy in preventing airborne transmission. To date, research on the face mask fit has been conducted mainly using experiments on limited subjects. The limited sample size in experimental studies makes it hard to reach a statistical correlation between mask fit and facial features in a population. Here, we employ a novel framework that utilizes a morphable face model and mask’s deployment simulation to test mask fit for many facial characteristics and mask designs. The proposed technique is an important step toward enabling personalized mask selection with maximum efficacy for society members.

Machine learning (ML) is a computerized analytical technique that is being increasingly employed in biomedicine. ML often provides an advantage over explicitly programmed strategies in the analysis of multidimensional information by recognizing relationships in the data that were not previously appreciated. As such, the use of ML in rheumatology is increasing, and numerous studies have employed ML to classify patients with rheumatic autoimmune inflammatory diseases (RAIDs) from medical records and imaging, biometric or gene expression data. However, these studies are limited by sample size, the accuracy of sample labelling, and absence of datasets for external validation. In addition, there is potential for ML models to overfit or underfit the data and, thereby, these models might produce results that cannot be replicated in an unrelated dataset. In this Review, we introduce the basic principles of ML and discuss its current strengths and weaknesses in the classification of patients with RAIDs. Moreover, we highlight the successful analysis of the same type of input data (for example, medical records) with different algorithms, illustrating the potential plasticity of this analytical approach. Altogether, a better understanding of ML and the future application of advanced analytical techniques based on this approach, coupled with the increasing availability of biomedical data, may facilitate the development of meaningful precision medicine for patients with RAIDs.

Modeling the relationship between some climatic determinants in the wet or cropping season of Makurdi, Benue State, Nigeria requires data aggregation. The consequence of this aggregation is the reduction in data sample size. This poses serious challenge of lack of model-fit when the Classical Linear Regression Modeling Approach is employed. The Bayesian Normal Regression Modeling Approach was therefore employed in surmounting this problem. Three Bayesian Normal Regression Models were fitted namely; the Solar radiation, Total Rainfall Amount and the Number of Dry Days model. Each model result was compared with that of its Classical model counterpart. The discrepancies observed were blamed on the sample size reduction. The results of the Bayesian models revealed that; Solar radiation increases by 0.791 MJ/m2 for each unit increase in the natural logarithm of Relative humidity. While it increases by 0.895 MJ/m2 for each unit increase in the natural logarithm of Wind speed. Total Rainfall Amount increases by 66.280 mm for each unit increase in the natural logarithm of the Number of Dry Days while it increases by 2.912 mm for each unit increase in the natural logarithm of the Number of Wet Days. Furthermore, the Number of Dry Days decreases by 6.905 days for each unit increase in the natural logarithm of Number of Wet days, while it increases by 2.028 days for each unit increase in the natural logarithm of Total Rainfall Amount. The study affirmed that the cropping season climate of Makurdi is becoming

PURPOSE To investigate emotional intelligence (EI) development in physician assistant (PA) students as they progress through their didactic education. METHODS Data were gathered through an online survey of EI distributed to a purposeful sample of 5 institutions with similar curriculum length and start dates. Program directors forwarded the survey to students at the start of their didactic education (pretest). Follow-up surveys were distributed via email to the students at the end of their didactic education (posttest). The survey consisted of 33 items related to 4 subscales of EI. Participants' age, gender, and previous healthcare experience were gathered. Five repeated measures ANOVAs were calculated for each EI summary score. Independent sample t-tests were conducted between pretest scores and a previously established EI mean. RESULTS A total of 192 first-year students were solicited. A sample of 68 (16 males; 52 females) served as participants. No results were attained for gender or age due to unbalanced sample sizes. Significant results were realized for total EI and the Managing Others' Emotions subscale. CONCLUSION Participants with more than one healthcare experience demonstrated significantly high emotional intelligence on the pretest. Participants with one healthcare experience demonstrated a significant increase in total EI and the Managing Others' Emotions subscale. The main limitation of the study was the attrition of participants between measures. Future research is needed to assess EI at the end of the clinical year, after a period of clinical experience, and to determine which educational activities are most likely to enhance EI.

The broad objective of the study is to examine the impact of Nigeria Fadama National development project on Agropreneur’s business development in Osun state, Nigeria. The sample size selected was Two hundred and seventy (270). Multi-stage sampling was adopted, and Simple random sampling design was used. Data collection method was a close-ended questionnaire. Linear Regression, Multiple Regression and Anova were used to test the Hypotheses of the study. The study shows that rural infrastructure variables used in the selected study area significantly predicted the level of Business Development, F (1,268) = 30.413, p < 0.05 F – statistical indicates that the overall regression model is highly statistically significant in terms of its goodness of fit since the value of Ftab (1,268) >Fcal (30.413). It also shows the magnitude of the difference, since the sig level is greater than 0.05 i.e 0.811, 0.985. The study reveals that only 0.9 per cent variance exists between the selected genders. In conclusion capacity building has really assisted farmers in adopting new technology in farming which led to an increase and expansion of their business outlets. The study recommends: Regular training for farmers to discover their skills in diversifying into various businesses within the agricultural sector using new technology should be encouraged by all stakeholders in business of food security and provision of grants to enable them expand their business desires.

Objective This study was aimed at establishing population norms of EQ-5D-Y in Japan by a nationwide large sample survey. Methods We performed a door-to-door survey by visiting the homes of children/adolescents aged 8–15 years selected by random sampling. The planned sample size was 3600 from 100 districts in Japan. Children/adolescents were asked to respond to the EQ-5D-Y instrument, and their parents, to background questions on themselves and their children. Summary statistics by age/sex were calculated to obtain the Japanese population norms. A multiple linear regression model was used to examine the relationships between the EQ-5D-Y index and their parents’ demographic factors, the children/adolescents’ diseases/symptoms and the family environment. Results We collected 3636 responses from 100 districts. The overall EQ-5D-Y index values (all sexes, ages) ranged from 0.90 to 0.95. The percentage of respondents reporting full health ranged from 40 to 60%. In regard to the influence of the children/adolescents’ diseases/symptoms on disutility, developmental disability showed the largest disutility values of 0.090. Sleeplessness and body pain were the symptoms that exerted the greatest influence on the EQ-5D-Y index; the effect sizes ranged from − 0.030 to − 0.098 for sleeplessness, and from − 0.023 to − 0.079 for body pain. The EQ-5D-Y index of children/adolescents with parents who reported severe stress was lower by 0.072 (p < 0.001), as compared with that of children/adolescents with parents reporting no stress. Conclusions Population norms of EQ-5D-Y were established for the first time. We also clarified the relationship between the EQ-5D-Y index value and the children/adolescents’ diseases/symptoms and the family environment.

We provide asymptotic theory for certain functions of the sample autocovariance matrices of a high-dimensional time series with infinite fourth moment. The time series exhibits linear dependence across the coordinates and through time. Assuming that the dimension increases with the sample size, we provide theory for the eigenvectors of the sample autocovariance matrices and find explicit approximations of a simple structure, whose finite sample quality is illustrated for simulated data. We also obtain the limits of the normalized eigenvalues of functions of the sample autocovariance matrices in terms of cluster Poisson point processes. In turn, we derive the distributional limits of the largest eigenvalues and functionals acting on them. In our proofs, we use large deviation techniques for heavy-tailed processes, point process techniques motivated by extreme value theory, and related continuous mapping arguments., 28 pages