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The need for a comparison between two proportions (sometimes called an A/B test) often arises in business, psychology, and the analysis of clinical trial data. Here we discuss two Bayesian A/B tests that allow users to monitor the uncertainty about a difference in two proportions as data accumulate over time. We emphasize the advantage of assigning a dependent prior distribution to the proportions (i.e., assigning a prior to the log odds ratio). This dependent-prior approach has been implemented in the open-source statistical software programs R and JASP. Several examples demonstrate how JASP can be used to apply this Bayesian test and interpret the results.

Northern Thailand is a hotspot for landslides. Rainfall-triggered landslides in this region have caused much suffering and many fatalities. In this work, a landslide-triggering rainfall threshold for Northern Thailand is proposed based on rainfall data relating to 48 triggering rainfall events that caused 59 landslides in the study area. To account for different mechanism of landslide formation, the threshold was portioned into two parts for different duration of rainfall events. A split point of 3 days was chosen as a separator for portioning the threshold to be 1) a threshold for rainfall events of duration no longer than 3 days and 2) a threshold for rainfall events of duration longer than 3 days. The threshold also required a suitable variable for antecedent rainfalls which was found to be cumulative rainfall over 25-day period (CR25) of 140 mm. Therefore, the thresholds combining cumulative rainfall with rainfall event - duration (CED) were established by incorporating the CR25 of 140 mm into the traditional ED threshold. This is the first attempt to incorporate the difference mechanism of landslide formation by dividing the CED threshold to two portions for difference rainfall duration. The introduced threshold shows positive sign of the prediction, particularly in term of false alarm rate, false alarm ratio, and critical success index. The introduced threshold will be useful for landslide warning system in the study area.

We aim to extend our investigations related to the Relative Intensity of Collaboration (RIC) indicator, by constructing a confidence interval for the obtained values.

This paper aims to identify risk factors and to determine the level of contamination of Pseudomonas aeruginosa by conventional Polymerase Chain Reaction (PCR) in beef commercialized in the markets of Huánuco, Peru. To meet this objective, an epidemiological study was carried out. The sample consisted of 300 biological analyses of beef meats in the markets of Huánuco. A sample was taken from each position, making a total of 300 during a few days. Observation guides were used in order to collect data. The determination of the presence of Pseudomonas aeruginosa was made by PCR. A statistical analysis was carried out using contingency tables and Chi-square Pearson's test, between the possible causes of contamination and the results obtained from the sample analysis. Pseudomonas aeruginosa was isolated in 69 samples out of a total of 300, corresponding to a frequency of 23%. Among the identified factors are: dirty uniform of another color (p=2.5469x10-13); dirty hands (p=0.000); work utensils in poor condition and dirty (p=3.4776x10-12); these factors were statistically significant to the frequency of Pseudomonas aeruginosa in beef. [ABSTRACT FROM AUTHOR]

This article serves as the third in a series that offers recommendations for optimal data reporting, specifically focusing on the statistical methods most frequently reported in Cytopathology articles. Measures of diagnostic accuracy were among the most commonly reported results in Cytopathology, with sensitivity and/or specificity reported in 32% of the reviewed articles. This article will provide a brief overview of common measures of diagnostic accuracy, including sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, overall diagnostic accuracy, receiver operating characteristic (ROC) curve, and area under the curve (AUC). Reporting recommendations for these measures will be reviewed, including the suggestion of providing a 2 × 2 contingency table when possible, or numerator and denominator values for calculations when all values needed for a contingency table are not known, and calculation of ROC and AUC if relevant. Additionally, paired measures should be reported, including sensitivity with specificity, positive with negative predictive values, and positive with negative likelihood ratios. Calculating 95% confidence intervals (CI) for the measures is recommended, with several methods to choose from, including the Wald interval, Wilson interval, Clopper‐Pearson interval, Agresti‐Coull interval, and Bayesian highest posterior density (HPD) interval. Since there are various methods for CI calculations, the author encourages the reader to consult with a trained statistician to identify the most appropriate method based on the data, which should be reported in the methods section of the resulting write‐up. [ABSTRACT FROM AUTHOR]

When examining the association between symmetrically associated categorical variables, correspondence analysis provides a visual means of identifying the structure of this association. An important and sometimes overlooked feature that can help the analyst determine whether these categories provide a statistically significant contribution to the association is the confidence region. When constructing these regions, correspondence analysis traditionally (but not always) considers Pearson's chi-squared statistic as the core measure of association between the variables. Such a statistic is a special case of the Cressie-Read family of divergence statistics as is the log-likelihood ratio statistic, Freedman-Tukey statistic, and other such measures. Therefore, this paper will consider the construction of confidence regions in correspondence analysis where this family of divergence statistics is used as the measure of association. Doing so provides a means of simply constructing confidence regions for each category of a contingency table and allows for such regions to be constructed when log-ratio analysis (LRA) or the Hellinger distance decomposition (HDD) method is applied to the contingency table. [ABSTRACT FROM AUTHOR]

This paper proposed the use of mutual information (MI) decomposition as a novel approach to identifying indispensable variables and their interactions for contingency table analysis. The MI analysis identified subsets of associative variables based on multinomial distributions and validated parsimonious log-linear and logistic models. The proposed approach was assessed using two real-world datasets dealing with ischemic stroke (with 6 risk factors) and banking credit (with 21 discrete attributes in a sparse table). This paper also provided an empirical comparison of MI analysis versus two state-of-the-art methods in terms of variable and model selections. The proposed MI analysis scheme can be used in the construction of parsimonious log-linear and logistic models with a concise interpretation of discrete multivariate data. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ciencia y Tecnología Agropecuaria is the property of Agrosavia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: Multiparametric magnetic resonance imaging (mpMRI) of the prostate gland is now the recommended initial investigation of choice for the detection of Prostate cancer (PCa). It effectively identifies patients who require prostate biopsies due to the risk of clinically significant PCa. It helps patients with clinically insignificant PCa avoid the invasive biopsies and possible accompanying complications. Large clinical trials have investigated the accuracy of mpMRI in detecting PCa. We performed a local review to examine the reliability of omitting tissue sampling in men with a negative (PIRADS 2 (P2) or less) mpMRI in the primary diagnostic setting. Methods: This was a retrospective study of patients with clinical suspicion of PCa within a 2-year period. Patients had a mpMRI prior to having trans-perineal prostate gland biopsies. Clinically significant disease was defined as Gleason 7 and above. The descriptive data was analysed using contingency table methods. A p-value less than 0.05 was statistically significant. Results: Out of 700 patients 90 had an mpMRI score of PIRADS 2. Seventy-seven (85.5%) of these patients had a negative biopsy, 9(10%) showed Gleason 6, 4 patients showed Gleason 7 or above. 78 patients with PIRADS 2 had a PSA density of < 0.15, none of which had a clinically significant biopsy result. The negative predictive value of mpMRI from this study is 95%. Conclusion: Our results are in line with negative predictive values demonstrated in the current literature. This local study, likely applicable to other district general hospitals, shows that mpMRI is a safe and reliable initial investigation to aid decisions on which patients require biopsies. [ABSTRACT FROM AUTHOR]

Assess cardiovascular health (CVH) during early childhood using the American Heart Association's recently updated construct, Life's Essential 8 (LE8); examine concordance in CVH status per LE8 versus Life's Simple 7 (LS7); and identify perinatal correlates of high CVH per LE8. We applied LE8 and LS7 to data from 305 children aged 4–7 years in Denver, CO; estimated % low, moderate, high, and optimal CVH; assessed concordance in CVH status based on LE8 and LS7 using contingency tables; and used multivariable logistic regression to identify early-life correlates of high CVH per LE8. Average age of children was 4.7 ± 0.6 years, 44.6% were female. No participants had low or optimal CVH, 43.9% had high, and 56.1% had moderate CVH per LE8, whereas 33.4% had high and 66.6% had moderate CVH per LS7. Twenty-two percent had high CVH based on both constructs. Correlates of high CVH were maternal prenatal diet quality (odds ratio Healthy Eating Index score>vs. ≤57 = 1.90 [1.12, 3.21]) and child age (odds ratio per 1 year = 1.58 [1.04. 2.42]). LE8 yielded higher prevalence of high CVH than LS7 during early childhood, though there is modest concordance between the two constructs. Maternal diet is a potential modifiable target to optimize early-life CVH. [ABSTRACT FROM AUTHOR]

Statistical analysis of categorical data often relies on multiway contingency tables; yet, as the number of categories and/or variables increases, the number of table cells with few (or zero) observations also increases. Unfortunately, sparse contingency tables invalidate the use of standard goodness-of-fit statistics. Limited-information fit statistics and bootstrapping procedures offer valuable solutions to this problem, but they present an additional concern in their strict reliance on the (potentially misleading) observed data. To address both of these issues, we demonstrate the Bayesian model checking technique, which yields insightful, useful, and comprehensive evaluations of specific properties of a given model. We illustrate this technique using item response data from a patient-reported psychopathology screening questionnaire, and we provide annotated R code to promote dissemination of this informative method in other prevention science modeling scenarios. [ABSTRACT FROM AUTHOR]

Social network monitoring has attracted the attention of many researchers in the area of statistical process monitoring. It is essential to consider the categorical attributes of communications between people in the modeling of social networks. Social network communications with categorical attributes can be summarized in contingency tables and it is more realistic to work with the communications as time-dependent variables. In the present study, since the autocorrelation between social networks can significantly alter the statistical performance of different monitoring approaches, generalized estimating equations are used to estimate model parameters considering autocorrelation between social networks. Moreover, two control charts, Hotelling's T2 and the multivariate exponentially weighted moving average, are developed to monitor model parameters in Phase II. The performance of the proposed method is evaluated through simulation studies in terms of the average run length criterion. Finally, the application of the proposed method is shown through a numerical example and a real case [ABSTRACT FROM AUTHOR]

This study aimed to validate the use of two SNP markers associated to a sdw1 allele identified previously in a short barley genotype (ND23049) with an adequate peduncle extrusion which reduces predisposition to fungal disease development. First, the GBS SNP were converted in a KASP marker but only one of them, named TP4712, correctly amplified all allelic variations and had a Mendelian segregation in a F2 population. To corroborate the association between TP4712 allele with plant height and peduncle extrusion, a total of 1221 genotypes were genotyped and evaluated for both traits. Out of the 1221 genotypes, 199 were F4 lines, 79 were a diverse panel, and 943 were two complete breeding cohorts of stage 1 yield trials. To corroborate the association between the sdw1 allele and the short plant height with adequate peduncle extrusion, contingency tables were created, grouping the 2427 data points into categories. Based on the contingency analysis, it was demonstrated that the higher proportion of short plants with adequate peduncle extrusion were present in genotypes carrying the SNP allele of ND23049 regardless the population and the sowing date. This study develops a marker-assisted selection tool to accelerate the introgression of favourable alleles for plant height and peduncle extrusion in adapted germplasm. [ABSTRACT FROM AUTHOR]

Copyright of Revista Española de Sociología is the property of Federacion Espanola de Sociologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Socioloski Pregled is the property of Srpsko Sociolosko Drustvo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to establish a relationship between HRM and innovation studies through human capital characteristics in order to achieve a better understanding of HRM's supportive role in innovation realization aligned with knowledge-based services. The study provides a new model of coordination between innovation modes of service sector firms and HR configuration adopted for managing people in these firms. By gathering data about the main variables from 132 Iranian knowledge-based service firms with more than 30 employees, all located in Tehran province (selected through systematic sampling), the status of every firm in the field of innovation mode and HR configuration was determined. The hypotheses were tested using contingency tables and binomial test. After testing hypotheses, it was found that the strongest alignment exists between market-oriented innovation and productivity-based HR configuration (at about 53%). The average value for the human capital characteristics in firms that had two mentioned statuses were more than another three statuses. To achieve ideal human capital management, managers of KBSFs need to pay more attention to the compatibility of their HR configurations with innovation modes of KBSFs in order to approach the satisfactory productivity level seen in such firms. [ABSTRACT FROM AUTHOR]

The 17 Sustainable Development Goals (SDGs) require the implementation of 167 targets aimed at eradicating poverty, protecting the planet and improving the quality of life of humankind. The United Nations calls for uniform sustainable development at the global, local and individual levels. This research pursues a twofold objective: first, to obtain evidence on the extent to which the achievement of the (SDGs) may be uniform across territories; second, to identify the socioeconomic characteristics that contribute to sustainable development. The empirical analysis has been carried out using clustering, cross efficiency and contingency tables applied to statistical information from 101 municipalities in Spain and Italy. The results provide evidence of inequalities between territories, revealing that only in the dimensions People (SDGs 1, 2, 3, 4, and 5) and Prosperity (SDGs 7, 8, 9, 10, and 11) has the desired homogeneity been attained. Notable differences are found in the degree of compliance with the other SDGs. Furthermore, it is shown that the socioeconomic characteristics associated with the geographical location contribute substantially to the gap between municipalities. In order to ensure countries' sustainable development, there is a need for environmental policies adapted to the specific features of each region. [ABSTRACT FROM AUTHOR]

Copyright of Revista FACE is the property of Universidad de Pamplona and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite a lack of evidence, a bone marrow aspirate differential of 500 cells is commonly used in the clinical setting. We aimed to test the performance of 200-cell counts for daily hematological workup. In total, 660 consecutive samples were analyzed recording differentials at 200 and 500 cells. Additionally, immunophenotype results and preanalytical issues were also evaluated. Clinical and statistical differences between both cutoffs and both methods were checked. An independent control group of 122 patients was included. All comparisons between both cutoffs and both methods for all relevant types of cells did not show statistically significant differences. No significant diagnostic discrepancies were demonstrated in the contingency table analysis. This is a real-life study, and some limitations may be pointed out, such as a different sample sizes according to the type of cell in the immunophenotype analysis, the lack of standardization of some preanalytical events, and the relatively small sample size of the control group. The comparisons of differentials by morphology on 200 and 500 cells, as well as by morphology (both cutoffs) and by immunophenotype, are equivalent from the clinical and statistical point of view. The preanalytical issues play a critical role in the assessment of bone marrow aspirate samples. [ABSTRACT FROM AUTHOR]

The purpose of the research is to evaluate and determine the magnitude of the socio-economic impact of artisan charcoal production on the quality of life of the population involved in the Manantay district of the Coronel Portillo province, Ucayali Region. The charcoal production has been a source of income since the wood boom, and this activity is practiced by small entrepreneurs, who were marginalized by pollution in urban areas of the Manantay District, hence, they choose to produce artisanal charcoal which is subject of the present study, for which it was carried out to estimate the trend of the productivity of artisanal charcoal in the district of Manantay, also, to determine the level of quality of life of the population involved in the production of artisanal charcoal and to determine the socio-economic impact of the artisanal production of charcoal in the district. We use a random sample consisting in 45 producers of charcoal, which responded a query based on a Likert scale. The results were represented in contingency tables and were processed with the support of the coefficient of Chi Square of Pearson. From the results obtained it is concluded that there is a socio-economic impact of the production of artisanal charcoal on the quality of life of the population involved in the Manantay district. [ABSTRACT FROM AUTHOR]

Identification of living undocumented individuals highlights the need for accurate, precise, and reproducible age estimation methods, especially in those cases involving minors. However, when their country of origin is unknown, or it can be only roughly estimated, it is extremely difficult to apply assessment policies, procedures, and practices that are accurate and child-sensitive. The main aim of this research is to optimize the correct classification of adults and minors by establishing new cut-off values for four different continents (Africa, America, Asia, and Europe). For this purpose, a vast sample of 10,701 orthopantomographs (OPTs) from four continents was evaluated. For determination and subsequent validation of the new third molar maturity index (I3M) cut-off values by world regions, a cross-validation by holdout method was used and contingency tables (confusion matrices) were generated. The lower third molar maturity indexes, from both left and right side (I3ML and I3MR) and the combination of both sides (I3ML_I3MR) were calculated. The new cut-off values, that aim to differentiate between a minor and an adult, with more than 74.00% accuracy for all populations were as follows (I3ML; I3MR; I3ML_I3MR, respectively): Africa = (0.10; 0.10; 0.10), America = (0.10; 0.09; 0.09), Asia = (0.15; 0.17; 0.14), and Europe = (0.09; 0.09; 0.09). The higher sensitivity (Se) was detected for the I3ML for male African people (91%) and the higher specificity (Sp) of all the parameters (I3ML; I3MR; I3ML_I3MR) for Europeans both male and female (> 91%). The original cut-off value (0.08) is still useful, especially in discriminating individuals younger than 18 years old which is the goal of the forensic methods used for justice. [ABSTRACT FROM AUTHOR]

The Adjusted Rand Index (ARI) is arguably one of the most popular measures for cluster comparison. The adjustment of the ARI is based on a hypergeometric distribution assumption which is not satisfactory from a modeling point of view because (i) it is not appropriate when the two clusterings are dependent, (ii) it forces the size of the clusters, and (iii) it ignores the randomness of the sampling. In this work, we present a new "modified" version of the Rand Index. First, as in Russell et al. (J Malar Inst India 3(1), 1940), we consider only the pairs consistent by similarity and ignore the pairs consistent by difference to define the MRI. Second, we base the adjusted version, called MARI, on a multinomial distribution instead of a hypergeometric distribution. The multinomial model is advantageous because it does not force the size of the clusters, correctly models randomness and is easily extended to the dependent case. We show that ARI is biased under the multinomial model and that the difference between ARI and MARI can be significant for small n but essentially vanishes for large n, where n is the number of individuals. Finally, we provide an efficient algorithm to compute all these quantities ((A)RI and M(A)RI) based on a sparse representation of the contingency table in our aricode package. The space and time complexity is linear with respect to the number of samples and, more importantly, does not depend on the number of clusters as we do not explicitly compute the contingency table. [ABSTRACT FROM AUTHOR]

Aim: to determine whether there is a relationship between attention to the special educational needs of gifted children in public, private and charter schools (concertados) in Andalusia and scholastic failure, as perceived by families. The GITTECALTASCAPACIDADESCAPACIDADESPA questionnaire (α =.901), with 71 variables, was used in a sample of N = 454 families in the Autonomous Community of Andalusia with gifted children attending primary schools. Frequency and correlation analysis (Pearson type) were applied, obtaining p values <.001, along with crosses of variables through contingency tables and a regression analysis with the main hypothesis, together with ANOVA tests. The data obtained from the families indicate that inadequate attention to the special educational needs of gifted children is closely related to academic failure and disappointing experiences at school suffered by gifted children generate in them negative associations with academics. [ABSTRACT FROM AUTHOR]

The research aim was to evaluate the Portuguese honey consumers' profile, their attitudes, perceptions, and trends towards the product, production, and consumption, to allow the development of marketing strategies. With this purpose, a questionnaire was developed in accordance with the Ajzen's Planned Behaviour Theory and was then completed by 784 interviewees to retrieve quantitative and qualitative data. These included demographic, consumption pattern, and behavioural pattern variables collected in a Likert scale. Spearman correlations were performed between ordinal and continuous variables, and chi-squared tests of independency applied to contingency tables between nominal variables. A positive correlation was found between age and frequency of purchasing. Men consume honey more frequently than women. Portuguese honey has a good reputation, and it is preferred in relation to imported honey. The Portuguese consumer is not completely aware of the different floral characteristics of honey, other hive products, and positive externalities associated with beekeeping. By filling the marketing gap identified, production and consumption of honey could be increased in Portugal. Marketing campaigns promoting the health benefits of honey and other hive products, as well as the externalities of beekeeping may be advantageous. [ABSTRACT FROM AUTHOR]

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight‐variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first‐line single‐agent chemotherapy resistance. FIGO is imperfect with one‐third of low‐risk patients developing disease resistance to first‐line single‐agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1‐6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland‐Altman calibration plots, decision curve analysis and contingency tables. M1‐6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P <.05); 55‐112 undertreated, 46‐206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment‐resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "A Statistical Forecasting Model for Extremes of the Fire Behaviour Index in Australia." The correction addresses errors in Figure 5 and Table 5 of the original publication. The corrected figure shows the forecast probability of extreme fire behavior index (FBI) using three ensemble members at two- and three-week hindcast lead times. The corrected table compares the accuracy, probability of detection, and false alarm ratio of the dynamical and statistical models. The correction emphasizes the importance of using multiple forecasting methods for fire danger forecasts. The scientific conclusions of the article remain unaffected. [Extracted from the article]

Background: To reduce pharmacy-related medical expenses, it is necessary to cut drug costs, potentially by increasing generic drug usage. This study analyzes the correlation between generic drug usage and monthly personal income by examining prescriptions for individual drugs. Methods: We conducted a cross-sectional study based on the data set from the National Database of Health Insurance Claims and Specific Health Checkups of Japan Open Data Japan and the Basic Survey on Wage Structure. We calculated the correlation coefficient between the usage rate of generic drugs in each prefecture of Japan and monthly personal incomes. We then analyzed the correlation coefficients based on the therapeutic categories of medicinal drugs; the contingency table was visualized as a mosaic plot. To compare the proportions between multiple categories, the chi-squared test was applied as a statistical significance test that was used in the analysis of n × m contingency tables. We worked with the null hypothesis that there were no differences between classes in the population. Results: Regarding the correlation coefficient between the usage rate of generic drugs and monthly personal incomes, the proportion of negative correlation coefficients for outpatient out-of-hospital and outpatient in-hospital prescriptions was over 70%, while that for inpatient prescriptions was 46.9%. The proportion of medicinal drugs exhibiting a negative correlation between the rates of generic drug usage and monthly personal incomes for outpatient out-of-hospital prescriptions and outpatient in-hospital prescriptions was higher than that of inpatient prescriptions. The proportion of statistically correlated medicinal drugs among inpatient prescriptions was lower than that among outpatient out-of-hospital and outpatient in-hospital prescriptions. The proportions of significant negative correlations for outpatient out-of-hospital, outpatient in-hospital, and inpatient prescriptions were 30.6%, 22.7%, and 3.5%, respectively. It was also observed that the rate of generic prescription usage for outpatient out-of-hospital and in-hospital prescriptions increased as monthly personal incomes decreased. In outpatients, the therapeutic categories with strong negative correlations were vasodilators and hyperlipidemia drugs. Conclusions: Our results may help to increase the usage rate of generic drugs in different prefectures by providing useful information for promoting them throughout Japan. [ABSTRACT FROM AUTHOR]

This study is a preliminary assessment of the latest version of the Global Satellite Measurement of Precipitation (GSMaP version 08) data, which were released in December 2021, for the Indonesian Maritime Continent (IMC), using rain gauge (RG) observations from December 2021 to June 2022. Assessments were carried out with 586 rain gauge (RG) stations using a point-to-pixel approach through continuous statistical and contingency table metrics. It was found that the coefficient correlation (CC) of GSMaP version 08 products against RG observations varied between low (CC = 0.14–0.29), moderate (CC = 0.33–0.45), and good correlation (CC = 0.72–0.75), for the hourly, daily, and monthly scales with a tendency to overestimate, indicated by a positive relative bias (RB). Even though the correlation of hourly data is still low, GSMaP can still capture diurnal patterns in the IMC, as indicated by the compatibility of the estimated peak times for the precipitation amount and frequency. GSMaP data also manage to observe heavy rainfall, as indicated by the good of detection (POD) values for daily data ranging from probability 0.71 to 0.81. Such a good POD value of daily data is followed by a relatively low false alarm ratio (FAR) (FAR < 0.5). However, the GSMaP overestimates light rainfall (R < 1 mm/day); as a consequence, it overestimates the consecutive wet days (CWD) and number of days with rainfall ≥ 1 mm (R1mm) indices, and underestimates the consecutive dry days (CDD) extreme rain index. GSMaP daily data accuracy depends on IMC's topographic conditions, especially for GSMaP real-time data. Of all GSMaP version 08 products evaluated, outperformed post-real-time non-gauge-calibrated (GSMaP_MVK), and followed by post-real-time gauge-calibrated (GSMaP_Gauge), near-real-time gauge-calibrated (GSMaP_NRT_G), near-real-time non-gauge-calibrated (GSMaP_NRT), real-time gauge-calibrated (GSMaP_Now_G), and real-time non-gauge-calibrated (GSMaP_Now). Thus, GSMaP near-real-time data have the potential for observing rainfall in IMC with faster latency. [ABSTRACT FROM AUTHOR]

The acceptance and widespread use of the Android operating system drew the attention of both legitimate developers and malware authors, which resulted in a significant number of benign and malicious applications available on various online markets. Since the signature-based methods fall short for detecting malicious software effectively considering the vast number of applications, machine learning techniques in this field have also become widespread. In this context, stating the acquired accuracy values in the contingency tables in malware detection studies has become a popular and efficient method and enabled researchers to evaluate their methodologies comparatively. In this study, we wanted to investigate and emphasize the factors that may affect the accuracy values of the models managed by researchers, particularly the disassembly method and the input data characteristics. Firstly, we developed a model that tackles the malware detection problem from a Natural Language Processing (NLP) perspective using Long Short-Term Memory (LSTM). Then, we experimented with different base units (instruction, basic block, method, and class) and representations of source code obtained from three commonly used disassembling tools (JEB, IDA, and Apktool) and examined the results. Our findings exhibit that the disassembly method and different input representations affect the model results. More specifically, the datasets collected by the Apktool achieved better results compared to the other two disassemblers. [ABSTRACT FROM AUTHOR]

Salinity tolerance is a determinant of a narrow or wide distribution range of organisms. Crayfishes are important key species in many aquatic environments so require a better understanding of their ability to live in different saline regimes. We identified all alien crayfish and examined their habitats (freshwater and/or saline) and origins to test whether these factors predict their dispersal. We used contingency tables populated with raw frequency data with χ2—tests and assessed statistical significance at α of 0.05. We identified 21 alien crayfishes and we found that alien crayfish species were disproportionately freshwater (71%), with significantly lower proportions of euryhaline crayfishes inhabiting freshwater to saline environments (29%). Alien crayfishes also significantly disproportionally originate from America (67% of these taxa) when compared to all 'other' grouped regions (33%). In total, 36% of American crayfishes represent euryhaline species inhabiting freshwater to saline habitats against only 14% of crayfishes from all "other" grouped regions. This suggests that binomial euryhalinity/origin can help understand the potential of spread. We discussed obtained results with known experimental data on salinity tolerance, osmoregulation, growth, and reproduction of American alien crayfish. The paper will help in the management of crayfish spread. [ABSTRACT FROM AUTHOR]

The problematic use of the Smartphone in adolescence is one of the main educational and social problems of today. In order to deepen this analysis, the following objectives were formulated: 1) Describe behaviors that indicate problematic use of the Smartphone; 2) Analyze the relationship between the frequency of use of the Smartphone and the indicators of problematic use; 3) Analyze the relationship between family supervision and indicators of problematic use of the Smartphone; 4) Analyze the predictors of technological stress. The sample consisted of 1,101 participants. A non-experimental survey-type quantitative design was chosen. A descriptive analysis was carried out and contingency tables, Chi Square, Cramer's V and Linear Regression analysis were used. The results showed that more than 30% of those surveyed stay up late using their mobile phones, 1 in 10 feel stressed if they do not receive messages or calls, and another 30% consider it easier to relate via the Internet. It concludes by emphasizing that the high frequency of use of the Smartphone causes imbalances in rest, irritability and stress levels in young people, while family supervision reduces the risks of suffering them. [ABSTRACT FROM AUTHOR]

The positive parenting approach has highlighted the importance of supporting families to perform the functions associated with their parental role and to improve children’s well-being. The aims of this study were to identify and describe the characteristics of family support programmes in Spain, and to examine the extent to which they meet evidence-based standards for programme formulation. The sample includes 57 programmes identified by the Spanish Family Support Network, which belongs to the pan-European Family Support Network(EurofamNet) . Frequency analyses and contingency tables were carried out. The results show that the Spanish programmes meet several evidence-based standards for programme formulation (i.e., manualization). However, further efforts are required in some areas, such as universality and interdisciplinarity of family support programmes. The findings provide a platform from which to design new initiatives in accordance with standards for prevention programmes, and inform stakeholders and politicians in drawing up evidencebased public policies. [ABSTRACT FROM AUTHOR]

In epistasis analysis, single-nucleotide polymorphism–single-nucleotide polymorphism interactions (SSIs) among genes may, alongside other environmental factors, influence the risk of multifactorial diseases. To identify SSI between cases and controls (i.e. binary traits), the score for model quality is affected by different objective functions (i.e. measurements) because of potential disease model preferences and disease complexities. Our previous study proposed a multiobjective approach-based multifactor dimensionality reduction (MOMDR), with the results indicating that two objective functions could enhance SSI identification with weak marginal effects. However, SSI identification using MOMDR remains a challenge because the optimal measure combination of objective functions has yet to be investigated. This study extended MOMDR to the many-objective version (i.e. many-objective MDR, MaODR) by integrating various disease probability measures based on a two-way contingency table to improve the identification of SSI between cases and controls. We introduced an objective function selection approach to determine the optimal measure combination in MaODR among 10 well-known measures. In total, 6 disease models with and 40 disease models without marginal effects were used to evaluate the general algorithms, namely those based on multifactor dimensionality reduction, MOMDR and MaODR. Our results revealed that the MaODR-based three objective function model, correct classification rate, likelihood ratio and normalized mutual information (MaODR-CLN) exhibited the higher 6.47% detection success rates (Accuracy) than MOMDR and higher 17.23% detection success rates than MDR through the application of an objective function selection approach. In a Wellcome Trust Case Control Consortium, MaODR-CLN successfully identified the significant SSIs (P  < 0.001) associated with coronary artery disease. We performed a systematic analysis to identify the optimal measure combination in MaODR among 10 objective functions. Our combination detected SSIs-based binary traits with weak marginal effects and thus reduced spurious variables in the score model. MOAI is freely available at https://sites.google.com/view/maodr/home. [ABSTRACT FROM AUTHOR]

The statistical independence between the reproductive stock and its corresponding recruitment to a fishery was tested for 43 stocks of clupeids in the Ransom Myers database by using the chi-squared test of a contingency table. The method was validated by simulating stock and recruitment (SR) contingency tables for data close to hypothetical SR curves that represent several known phenomena. The clupeid SR data were grouped by the criteria of percentile points to build the contingency tables. The independence test of the clupeid stocks was rejected in only 15 cases, thus the independence hypothesis was sustained in the remaining 28 cases. This demonstrates that fitting an SR model in these clupeid stocks is not justified because their abundance could be affected by several causes other than reproductive stock fluctuations. [ABSTRACT FROM AUTHOR]

Forecasts of discrete events, such as precipitation, dust storms, and typhoons, can be deterministic, categorical, or probabilistic. Ensemble-based probabilistic predictions generate more consistent forecasts than individual deterministic models. We introduce and evaluate the Ensemble Prediction System of Asian Dust Aerosol Model 3, which generates probability forecasts of Asian dust. Probability forecasts were produced for 300 µgm-3 PM10 mass concentrations, according to the air-quality standards of the Ministry of Environment of South Korea and Korea Meteorological Administration. Crisis-level information was produced to categorize the dust risk level for Asia, using a risk matrix. The model's performance was evaluated using a 2 × 2 contingency table, the Brier skill score, and a reliability diagram. For skill score evaluation via the contingency table, the average hit rate and threat score were 0.46 and 0.34 for the best three sites, Jurihe, Erenhot, and Wulatezhongqi. The Brier skill score was positive for approximately 60% of stations, with the highest (0.410) and lowest (-2.038) values in Erenhot and Yanan, respectively. The reliability diagram revealed overestimated Asian dust frequencies for all stations. Although the stations were located within the same regions, their skill scores differed. Regional characteristics of skill scores should be further investigated in the future. [ABSTRACT FROM AUTHOR]

In categorical data analysis, the 2 × 2 contingency tables are commonly used to assess the association between groups and responses, this is achieved by using some measures of association, such as the contingency coefficient, odds ratio, risk relative, etc. In a Bayesian approach, the risk ratio is modeled according to a Beta-Binomial model, which has exact posterior distribution, due to the conjugacy property of the model. In this work, we provide the exact posterior distribution of the relative risk for the non-conjugate Kumaraswamy--Binomial model. The results are based on special functions and we give exact expressions for the posterior density, moments, and cumulative distribution. An example illustrates the theory. [ABSTRACT FROM AUTHOR]

Background: Outcome reporting bias in individual trials can compromise the validity of pooled estimates within systematic reviews. Recent strategies have attempted to address outcome reporting bias, which favours the full reporting of statistically significant outcomes over non-significant outcomes. We examined whether the association between full outcome reporting and statistical significance in surgical trials has changed from 2009 to 2019. Methods: We systematically searched for 350 surgical randomized controlled trials (RCTs) from 2009 and 350 surgical RCTs from 2019. Outcomes were classified as fully reported, partially reported, qualitatively reported or unreported. For each outcome, a contingency table was populated with full outcome reporting (yes/no) and statistical significance (yes/no). We combined odds ratios in random effects meta-analysis to estimate the association between full outcome reporting and statistical significance in 2009 compared with 2019. Results: Twenty-eight percent of outcomes in 2009 were incompletely reported, compared with 30% in 2019. In 2009, significant outcomes were more likely to be fully reported than non-significant outcomes (OR = 2.4, 95% CI 1.7–3.4, I2 = 35%), but the opposite association was seen in 2019 (OR = 0.51, 95% CI 0.34–0.77, I2 = 43%). RCTs from 2019 were less likely to demonstrate outcome reporting bias favouring significant outcomes (OR = 0.21, 95% CI 0.12–0.35, P < 0.001). Conclusion: Outcome reporting bias favouring the full reporting of significant over nonsignificant outcomes was demonstrated in 2009, but the opposite association was seen in 2019. There remains a high prevalence of incomplete outcome reporting. We recommend ongoing adherence to trial protocol guidelines to improve outcome reporting transparency and completeness. [ABSTRACT FROM AUTHOR]

Let G be a finite group. Let H,K be subgroups of G and H∖G/K the double coset space. Let Q be a probability on G which is constant on conjugacy classes (Q(s-1ts)=Q(t)). The random walk driven by Q on G projects to a Markov chain on H∖G/K. This allows analysis of the lumped chain using the representation theory of G. Examples include coagulation-fragmentation processes and natural Markov chains on contingency tables. Our main example projects the random transvections walk on GLn(q) onto a Markov chain on Sn via the Bruhat decomposition. The chain on Sn has a Mallows stationary distribution and interesting mixing time behavior. The projection illuminates the combinatorics of Gaussian elimination. Along the way, we give a representation of the sum of transvections in the Hecke algebra of double cosets. Some extensions and examples of double coset Markov chains with G a compact group are discussed. [ABSTRACT FROM AUTHOR]

Background Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination. Results We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles. Conclusion GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer. [ABSTRACT FROM AUTHOR]

This paper summarises the results of an inventory of abandoned underground mines within the Nízký Jeseník Upland (Czechia, Central Europe). The area has a long and complex history of mining. During the period between the 11th and 13th centuries, the upland was the centre of ore mining, and later, during the 18th and 19th centuries, it transitioned into slate mining for roofing. From 2016 through 2018, we collected detailed data from 137 mines to better understand their parameters and functioning within the contemporary landscape. The data were mainly focused on the geomorphic character of underground mines, as the existing inventories focus on various other aspects. The results were processed into an interactive web map using ArcGIS Online’s online mapping software. Relations between parameters were assessed using three methods: the χ2 test for a contingency table, ANOVA and linear regression. [ABSTRACT FROM AUTHOR]

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We herein propose a PraNet-based deep-learning model for estimating the size of non-perfusion area (NPA) in pseudo-color fundus photos from an ultra-wide-field (UWF) image. We trained the model with focal loss and weighted binary cross-entropy loss to deal with the class-imbalanced dataset, and optimized hyperparameters in order to minimize validation loss. As expected, the resultant PraNet-based deep-learning model outperformed previously published methods. For verification, we used UWF fundus images with NPA and used Bland–Altman plots to compare estimated NPA with the ground truth in FA, which demonstrated that bias between the eNPA and ground truth was smaller than 10% of the confidence limits zone and that the number of outliers was less than 10% of observed paired images. The accuracy of the model was also tested on an external dataset from another institution, which confirmed the generalization of the model. For validation, we employed a contingency table for ROC analysis to judge the sensitivity and specificity of the estimated-NPA (eNPA). The results demonstrated that the sensitivity and specificity ranged from 83.3–87.0% and 79.3–85.7%, respectively. In conclusion, we developed an AI model capable of estimating NPA size from only an UWF image without angiography using PraNet-based deep learning. This is a potentially useful tool in monitoring eyes with ischemic retinal diseases. [ABSTRACT FROM AUTHOR]

A test of independence is commonly used to determine differences (or associations) between samples in a nominal level measurement. Fisher's exact test and Chi-square test are two of the most widely applied tests of independence used in the data analyses in different areas such as information technologies, biostatistics, psychology and health sciences. In some cases, contingency tables with null entries (also called random zeros) arise, particularly if the number of samples is small, and the variables analyzed are multilevel. This situation becomes a problem because if one or more entries in a contingency table are zero or have small values, then the tests of independence produce unreliable results. In this paper, we propose a method to address that issue. The method merges one or more levels of the variables analyzed to create contingency tables with only one degree of freedom, avoiding applying a test of independence on contingency tables with random zeros. The source code (Python) of the method is publicly available for use. The results obtained using our method give a complete panorama of the associations between the variables of a data set. To show the effectiveness of our approach to find dependencies between variables, we use four data sets publicly available on the Internet. [ABSTRACT FROM AUTHOR]

This study focuses on R x R ordinal square contingency tables. Ordinal square contingency tables are always obtained by cross-classifying the matched-pair data of the two ordinal categorical variables with the same classifications. A well-known model in square contingency tables is the symmetry model. This study focuses on the relationship between the symmetry and sum-symmetry models. The sum-symmetry model has a symmetric structure between the probability that the sum of row variable X and column variable Y is t, when X < Y, for t = 3, . . ., 2R -- 1 and the probability that the sum of X and Y is t, when X > Y . The sum-symmetry model inevitably holds when the symmetry model holds, but the converse is not necessarily true. This study proposes a model that must be satisfied in addition to the sum-symmetry model, to satisfy the symmetry model. We also reveal that the value of the likelihood ratio chi-squared statistic of the symmetry model is equal to the sum of chi-squared statistic of the sumand sum-parameter symmetry models. We evaluate the utility of these properties by applying them to real-world vision data. [ABSTRACT FROM AUTHOR]