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Based on periodogram‐ratios of two univariate time series at different frequency points, two tests are proposed for comparing their spectra. One is an Anderson–Darling‐like statistic for testing the equality of two time‐invariant spectra. The other is the maximum of Anderson–Darling‐like statistics for testing the equality of two time‐varying spectra. Both of two tests are applicable for independent or dependent time series. Several simulation examples show that the proposed statistics outperform those that are also based on periodogram‐ratios but constructed by the Pearson‐like statistics. [ABSTRACT FROM AUTHOR]

Proportional odds models are commonly used to model ordinal responses, but the proportional odds assumption may not hold in practice, leading to biased inference. Tests such as score, Wald and likelihood ratio (LR) have been proposed to evaluate the proportional odds assumption based on models without the assumption. Brant has proposed an independent binary model-based Wald-type test, and Wolfe and Gould have extended the idea to propose an LR-type test. This paper provides a brief review of the Brant and Wolfe-Gould tests for evaluating the proportional odds assumption and evaluates their performance through simulation studies and a real data example. Sample programs are provided in SAS, SPSS and Stata to facilitate the implementation of these tests using standard statistical software packages. This study highlights the importance of evaluating the proportional odds assumption when using proportional odds models for ordinal responses. The sample programs provided in this paper make it easy for researchers to apply these tests in their own analyses using standard statistical software packages. [ABSTRACT FROM AUTHOR]

Data with censored initiating and terminating times arises quite frequently in acquired immunodeficiency syndrome (AIDS) epidemiologic studies. Analysis of such data involves a complicated bivariate likelihood, which is difficult to deal with computationally. Bayesian analysis, on the other hand, presents added complexities that have yet to be resolved. By exploiting the simple form of a complete data likelihood and utilizing the power of a Markov Chain Monte Carlo (MCMC) algorithm, this paper presents a methodology for fitting Bayesian regression models to such data. The proposed methods extend the work of Sinha (1997), who considered non-parametric Bayesian analysis of this type of data. The methodology is illustrated with an application to a cohort of HFV infected hemophiliac patients. [ABSTRACT FROM AUTHOR]

This article proposes a distance‐based framework incentivized by the paradigm shift toward feature aggregation for high‐dimensional data, which does not rely on the sparse‐feature assumption or the permutation‐based inference. Focusing on distance‐based outcomes that preserve information without truncating any features, a class of semiparametric regression has been developed, which encapsulates multiple sources of high‐dimensional variables using pairwise outcomes of between‐subject attributes. Further, we propose a strategy to address the interlocking correlations among pairs via the U‐statistics‐based estimating equations (UGEE), which correspond to their unique efficient influence function (EIF). Hence, the resulting semiparametric estimators are robust to distributional misspecification while enjoying root‐n consistency and asymptotic optimality to facilitate inference. In essence, the proposed approach not only circumvents information loss due to feature selection but also improves the model's interpretability and computational feasibility. Simulation studies and applications to the human microbiome and wearables data are provided, where the feature dimensions are tens of thousands. [ABSTRACT FROM AUTHOR]

Considers a missing-data formulation for the regression analysis of survival data with censored initiating and terminating times. Use of EM-types algorithms to simplify maximum likelihood estimates computation; Formulation and interference under the missing-data approach; Real-data analysis application involving a HIV-infected hemophiliac patients cohort.

Although much work has been done on comparing and contrasting the EM and ECME algorithms, in terms of their rates of convergence, it is not clear what mechanism underlies each and, furthermore, what factors may determine and influence their rates of convergence. In this paper, we examine the convergence rates and properties of these two popular optimisation algorithms as used in computing the maximum likelihood estimates from regression models with t-distributed errors. By approaching this computing problem through the use of two data augmentation schemes, as well as variations of these well-known algorithms, we offer a more composite view on the performance of each. [ABSTRACT FROM AUTHOR]

Two tests are proposed in this paper for comparing spectra of two univariate time series. One is a Pearson‐like statistic based only on periodograms of the compared time series and applicable for testing the equality of two time‐invariant spectra of two independent or dependent time series, with an asymptotic chi‐squared distribution under the null hypothesis. The other is based on the maximum of the Pearson‐like statistics. Not only does this test, again, depend only on periodograms but also approximately equals the maximum of a chi‐squared distribution of the same degrees of freedom under the null. It can be used to test the equality of spectra of two locally stationary time series regardless of whether they are dependent or independent. Multiple simulation examples show that both statistics achieve good performance. The proposed approach is illustrated by an application to longitudinal vibration data from a container ship. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Anti-obesity bias is pervasive among medical professionals, students, and trainees. Stigmatization of patients leads to suboptimal care and clinical outcomes. Educational strategies in medical training are needed to reverse these attitudes. The aim of this study was to evaluate the effect of an innovative didactic intervention and a standardized patient (SP) exercise on attitudes towards patients with obesity among medical students. METHODS: In 2016, a quasi-experimental study design was used at a US medical school. The class was divided into 2 groups according to a pre-determined protocol based on their clinical schedule, one assessed after exposure to a SP group and the other after exposure to the SP and an interactive lecture (IL + SP group) with real patients. The Attitudes about Treating Patients with Obesity and The Perceived Causes of Obesity questionnaires measured changes in several domains. A generalized estimating equations model was used to estimate the effect of the interventions both within and between groups. RESULTS: Both groups showed improvements in negative and positive attitudes, although the reduction in scores for the negative attitude domain did not reach statistical significance in the IL + SP group (for the SP group, P =.01 and <.001, respectively; for the IL + SP group, P =.15 and.01, respectively). For perceived causes of obesity, there were no statistically significant changes for pre–post survey measures within each group, except for the physiologic causes domain in the SP group (P =.03). The addition of an IL to a SP curriculum did not result in any changes for any domain in between-group analyses. CONCLUSIONS: Although adding a novel intervention utilizing real patients to a SP curriculum failed to show an additional educational benefit, our study showed that it is possible to influence attitudes of medical students regarding patients with obesity. [ABSTRACT FROM AUTHOR]

BACKGROUND: Herbicides are the most used class of pesticides worldwide, and insect repellents are widely used globally. Yet, there is a dearth of studies characterizing the associations between these chemical groups and human neurobehavior. Experimental studies suggest that glyphosate and 2,4-dichlorophenoxyacetic acid (2,4-D) herbicides can affect neurobehavior and the cholinergic and glutamatergic pathways in the brain. We aim to assess whether herbicides and insect repellents are associated with neurobehavioral performance in adolescents. METHODS: We assessed 519 participants (11-17 years of age) living in agricultural communities in Ecuador. We quantified urinary concentrations of glyphosate, 2,4-D, and two N,N-diethyl-meta-toluamide (DEET) insect repellent metabolites [3-(diethylcarbamoyl)benzoic acid (DCBA) and 3-(ethylcarbamoyl) benzoic acid (ECBA)] using isotope-dilution mass spectrometry. We assessed neurobehavioral performance using 9 subtests across 5 domains (attention/inhibitory control, memory/learning, language, visuospatial processing, and social perception). We characterized the associations using generalized estimating equations and multiple imputation for metabolites below detection limits. Models were adjusted for demographic and anthropometric characteristics, urinary creatinine, and sexual maturation. Mediation by salivary cortisol, dehydroepiandrosterone, 17β-estradiol, and testosterone was assessed using structural equation modeling. RESULTS: The mean of each neurobehavioral domain score was between 7.0 and 8.7 [standard deviation (SD) range: 2.0-2.3]. Glyphosate was detected in 98.3% of participants, 2,4-D in 66.2%, DCBA in 63.3%, and ECBA in 33.4%. 2,4-D was negatively associated with all neurobehavioral domains, but statistically significant associations were observed with attention/inhibition [score difference per 50% higher metabolite concentration (β)= -0.19 95% confidence interval (CI): -0.31, -0.07], language [β= -0.12 (95% CI: -0.23, -0.01)], and memory/learning [β= -0.11 (95% CI: -0.22, 0.01)]. Glyphosate had a statistically significant negative association only with social perception [β= -0.08 (95% CI: -0.14, -0.01)]. DEET metabolites were not associated with neurobehavioral performance. Mediation by gender and adrenal hormones was not observed. CONCLUSION: This study describes worse neurobehavioral performance associated with herbicide exposures in adolescents, particularly with 2,4-D. Replication of these findings among other pediatric and adult populations is needed. [ABSTRACT FROM AUTHOR]

Background: Patterns of survey response and the characteristics associated with response over time in longitudinal studies are important to discern for the development of tailored retention efforts aimed at minimizing response bias. The Millennium Cohort Study, the largest and longest running cohort study of military personnel and veterans, is designed to examine the long-term health effects of military service and experiences and thus relies on continued participant survey responses over time. Here, we describe the response rates for follow-up survey data collected over 15 years and identify characteristics associated with follow-up survey response and mode of response (paper vs. web). Method: Patterns of follow-up survey response and response mode (web, paper, none) were examined among eligible participants (n=198,833), who were initially recruited in four panels from 2001 to 2013 in the Millennium Cohort Study, for a follow-up period of 3–15 years (2004–2016). Military and sociodemographic factors (i.e., enrollment panel, sex, birth year, race and ethnicity, educational attainment, marital status, service component, service branch, pay grade, military occupation, length of service, and time deployed), life experiences and health-related factors (i.e., military deployment/combat experience, life stressors, mental health, physical health, and unhealthy behaviors) were used to examine follow-up response and survey mode over time in multivariable generalized estimating equation models. Results: Overall, an average response rate of 60% was observed across all follow-up waves. Factors associated with follow-up survey response over time included increased educational attainment, married status, female sex, older age, military deployment (regardless of combat experience), and higher number of life stressors, mental health issues, and physical health diagnoses. Conclusion: Despite the challenges associated with collecting multiple waves of follow-up survey data from members of the U.S. military during and after service, the Millennium Cohort Study has maintained a relatively robust response rate over time. The incorporation of tailored messages and outreach to those groups least likely to respond over time may improve retention and thereby increase the representativeness and generalizability of collected survey data. [ABSTRACT FROM AUTHOR]

Background: Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) measures of ambient air pollution are associated with accelerated age-related cognitive impairment, and Alzheimer's disease and related dementias (ADRD). Objective: We examined associations between air pollution, four cognitive factors, and the moderating role of apolipoprotein E (APOE) genotype in the understudied period of midlife. Methods: Participants were ∼1,100 men in the Vietnam Era Twin Study of Aging. Baseline cognitive assessments were from 2003 to 2007. Measures included past (1993–1999) and recent (3 years prior to baseline assessment) PM2.5 and NO2 exposure, in-person assessment of episodic memory, executive function, verbal fluency, and processing speed, and APOE genotype. Average baseline age was 56 years with a 12-year follow-up. Analyses adjusted for health and lifestyle covariates. Results: Performance in all cognitive domains declined from age 56 to 68. Higher PM2.5 exposures were associated with worse general verbal fluency. We found significant exposure-by-APOE genotype interactions for specific cognitive domains: PM2.5 with executive function and NO2 with episodic memory. Higher PM2.5 exposure was related to worse executive function in APOE ɛ4 carriers, but not in non-carriers. There were no associations with processing speed. Conclusion: These results indicate negative effects of ambient air pollution exposure on fluency alongside intriguing differential modifications of cognitive performance by APOE genotype. APOE ɛ4 carriers appeared more sensitive to environmental differences. The process by which air pollution and its interaction with genetic risk for ADRD affects risk for later life cognitive decline or progression to dementia may begin in midlife. [ABSTRACT FROM AUTHOR]

Although logistic regression is the most popular for modelling regression relationships with binary responses, many find relative risk (RR), or risk ratio, easier to interpret and prefer to use this measure of risk in regression analysis. Indeed, since Zou published his modified Poisson regression approach for modelling RR for cross-sectional data, his paper has been cited over 7 000 times, demonstrating the popularity of this alternative measure of risk in regression analysis involving binary responses. As longitudinal studies have become increasingly popular in clinical trials and observational studies, it is imperative to extend Zou's approach for longitudinal data. The two most popular approaches for longitudinal data analysis are the generalised linear mixed-effects model (GLMM) and generalised estimating equations (GEE). However, the parametric GLMM cannot be used for the extension within the current context, because Zou's approach treats the binary response as a Poisson variable, which is at odds with the Bernoulli distribution for the binary response. On the other hand, as it imposes no mathematical model on data distributions, the semiparametric GEE is coherent with Zou's modified Poisson regression. In this paper, we develop a GEE-based longitudinal model for binary responses to provide inference about RR. [ABSTRACT FROM AUTHOR]

Objective: To determine associations of alcohol use with cognitive aging among middle-aged men. Method: 1,608 male twins (mean 57 years at baseline) participated in up to three visits over 12 years, from 2003–2007 to 2016–2019. Participants were classified into six groups based on current and past self-reported alcohol use: lifetime abstainers, former drinkers, very light (1–4 drinks in past 14 days), light (5–14 drinks), moderate (15–28 drinks), and at-risk drinkers (>28 drinks in past 14 days). Linear mixed-effects regressions modeled cognitive trajectories by alcohol group, with time-based models evaluating rate of decline as a function of baseline alcohol use, and age-based models evaluating age-related differences in performance by current alcohol use. Analyses used standardized cognitive domain factor scores and adjusted for sociodemographic and health-related factors. Results: Performance decreased over time in all domains. Relative to very light drinkers, former drinkers showed worse verbal fluency performance, by –0.21 SD (95% CI –0.35, –0.07), and at-risk drinkers showed faster working memory decline, by 0.14 SD (95% CI 0.02, –0.20) per decade. There was no evidence of protective associations of light/moderate drinking on rate of decline. In age-based models, light drinkers displayed better memory performance at advanced ages than very light drinkers (+0.14 SD ; 95% CI 0.02, 0.20 per 10-years older age); likely attributable to residual confounding or reverse association. Conclusions: Alcohol consumption showed minimal associations with cognitive aging among middle-aged men. Stronger associations of alcohol with cognitive aging may become apparent at older ages, when cognitive abilities decline more rapidly. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Anti-obesity bias is pervasive among medical professionals, students, and trainees. Stigmatization of patients leads to suboptimal care and clinical outcomes. Educational strategies in medical training are needed to reverse these attitudes. The aim of this study was to evaluate the effect of an innovative didactic intervention and a standardized patient (SP) exercise on attitudes towards patients with obesity among medical students. METHODS: In 2016, a quasi-experimental study design was used at a US medical school. The class was divided into 2 groups according to a pre-determined protocol based on their clinical schedule, one assessed after exposure to a SP group and the other after exposure to the SP and an interactive lecture (IL+SP group) with real patients. The Attitudes about Treating Patients with Obesity and The Perceived Causes of Obesity questionnaires measured changes in several domains. A generalized estimating equations model was used to estimate the effect of the interventions both within and between groups. RESULTS: Both groups showed improvements in negative and positive attitudes, although the reduction in scores for the negative attitude domain did not reach statistical significance in the IL +SP group (for the SP group, P=.01 and < .001, respectively; for the IL+SP group, P= .15 and .01, respectively). For perceived causes of obesity, there were no statistically significant changes for pre-post survey measures within each group, except for the physiologic causes domain in the SP group (P=.03). The addition of an IL to a SP curriculum did not result in any changes for any domain in between-group analyses. CONCLUSIONS: Although adding a novel intervention utilizing real patients to a SP curriculum failed to show an additional educational benefit, our study showed that it is possible to influence attitudes of medical students regarding patients with obesity. [ABSTRACT FROM AUTHOR]

Patients with non-alcoholic fatty liver disease (NAFLD) and significant fibrosis (fibrosis stage ≥2) are candidates for pharmacological trials. The aim of this study was to perform a head-to-head comparison of the diagnostic test characteristics of three non-invasive stiffness-based models including MEFIB (magnetic resonance elastography [MRE] plus FIB-4), MAST (magnetic resonance imaging [MRI]-aspartate aminotransferase [AST]), and FAST (FibroScan-AST) for detecting significant fibrosis. This prospective study included 563 patients with biopsy-proven NAFLD undergoing contemporaneous MRE, MRI proton density fat fraction (MRI-PDFF) and FibroScan from two prospective cohorts derived from Southern California and Japan. Diagnostic performances of models were evaluated by area under the receiver-operating characteristic curve (AUC). The mean age of the cohort was 56.5 years (51% were women). Significant fibrosis was observed in 51.2%. To detect significant fibrosis, MEFIB outperformed both MAST and FAST (both p <0.001); AUCs for MEFIB, MAST, and FAST were 0.901 (95% CI 0.875–0.928), 0.770 (95% CI 0.730–0.810), and 0.725 (95% CI 0.683–0.767), respectively. Using rule-in criteria, the positive predictive value of MEFIB (95.3%) was significantly higher than that of FAST (83.5%, p = 0.001) and numerically but not statistically greater than that of MAST (90.0%, p = 0.056). Notably, MEFIB's rule-in criteria covered more of the study population than MAST (34.1% vs. 26.6%; p = 0.006). Using rule-out criteria, the negative predictive value of MEFIB (90.1%) was significantly higher than that of either MAST (69.6%) or FAST (71.8%) (both p < 0.001). Furthermore, to diagnose "at risk" non-alcoholic steatohepatitis defined as NAFLD activity score ≥4 and fibrosis stage ≥2, MEFIB outperformed both MAST and FAST (both p < 0.05); AUCs for MEFIB, MAST, and FAST were 0.768 (95% CI 0.728–0.808), 0.719 (95% CI 0.671–0.766), and 0.687 (95% CI 0.640–0.733), respectively. MEFIB was better than MAST and FAST for detection of significant fibrosis as well as "at risk" NASH. All three models provide utility for the risk stratification of NAFLD. Non-alcoholic fatty liver disease (NAFLD) affects over 25% of the general population worldwide and is one of the main causes of chronic liver disease. Because so many individuals have NAFLD, it is not practical to perform liver biopsies to identify those with more severe disease who may require pharmacological interventions. Therefore, accurate non-invasive tests are crucial. Herein, we compared three such tests and found that a test called MEFIB was the best at detecting patients who might require treatment. [Display omitted] • Patients with NAFLD and significant fibrosis (fibrosis stage ≥2) are candidates for pharmacological trials. • We performed a head-to-head comparison of the diagnostic test characteristics of three non-invasive stiffness-based models. • To detect significant fibrosis, MEFIB outperformed both MAST and FAST (both p <0.001). • MEFIB demonstrated a robust PPV (95%) and NPV (90%), and should be used in a two-step strategy to identify significant fibrosis. [ABSTRACT FROM AUTHOR]

This study introduces a flexible, adhesive-integrated electrode array that was developed to enable non-invasive monitoring of cervical nerve activity. The device uses silver-silver chloride as the electrode material of choice and combines it with an electrode array consisting of a customized biopotential data acquisition unit and integrated graphical user interface (GUI) for visualization of real-time monitoring. Preliminary testing demonstrated this electrode design can achieve a high signal to noise ratio during cervical neural recordings. To demonstrate the capability of the surface electrodes to detect changes in cervical neuronal activity, the cold-pressor test (CPT) and a timed respiratory challenge were employed as stressors to the autonomic nervous system. This sensor system recording, a new technique, was termed Cervical Electroneurography (CEN). By applying a custom spike sorting algorithm to the electrode measurements, neural activity was classified in two ways: (1) pre-to-post CPT, and (2) during a timed respiratory challenge. Unique to this work: (1) rostral to caudal channel position-specific (cephalad to caudal) firing patterns and (2) cross challenge biotype-specific change in average CEN firing, were observed with both CPT and the timed respiratory challenge. Future work is planned to develop an ambulatory CEN recording device that could provide immediate notification of autonomic nervous system activity changes that might indicate autonomic dysregulation in healthy subjects and clinical disease states. [ABSTRACT FROM AUTHOR]

Complex disorders usually affect multiple symptom domains measured by several outcomes. The importance of these outcomes is often different among patients. Current approaches integrate multiple outcomes without considering patient preferences at the individual level. In this article, we propose a new composite Desirability of Outcome Ranking (DOOR) that integrates individual level ranking of outcome importance and define a winning probability measuring the overall treatment effect. Stratified randomization can be performed based on the participants' baseline outcome rankings. A Wilcoxon-Mann-Whitney U-statistic is used to average the pairwise DOOR between one treated and one control patient, considering the difference in these patients' ranking of outcome importance. We use both theoretical and empirical methods to examine the statistical properties of our method and to compare with conventional approaches. We conclude that the proposed composite DOOR properly reflects patient-level preferences and can be used in pivotal trials or comparative effectiveness trials for a patient-centered evaluation of overall treatment benefits. [ABSTRACT FROM AUTHOR]

Background: Cognitive reserve and resilience are terms used to explain interindividual variability in maintenance of cognitive health in response to adverse factors, such as brain pathology in the context of aging or neurodegenerative disorders. There is substantial interest in identifying tractable substrates of resilience to potentially leverage this phenomenon into intervention strategies. One way of operationalizing cognitive resilience that has gained popularity is the residual method: regressing cognition on an adverse factor and using the residual as a measure of resilience. This method is attractive because it provides a statistical approach that is an intuitive match to the reserve/resilience conceptual framework. However, due to statistical properties of the regression equation, the residual approach has qualities that complicate its interpretation as an index of resilience and make it statistically inappropriate in certain circumstances. Methods and results: We describe statistical properties of the regression equation to illustrate why the residual is highly correlated with the cognitive score from which it was derived. Using both simulations and real data, we model common applications of the approach by creating a residual score (global cognition residualized for hippocampal volume) in individuals along the AD spectrum. We demonstrate that in most real-life scenarios, the residual measure of cognitive resilience is highly correlated with cognition, and the degree of this correlation depends on the initial relationship between the adverse factor and cognition. Subsequently, any association between this resilience metric and an external variable may actually be driven by cognition, rather than by an operationalized measure of resilience. We then assess several strategies proposed as potential solutions to this problem, such as including both the residual and original cognitive measure in a model. However, we conclude these solutions may be insufficient, and we instead recommend against "pre-regression" strategies altogether in favor of using statistical moderation (e.g., interactions) to quantify resilience. Conclusions: Caution should be taken in the use and interpretation of the residual-based method of cognitive resilience. Rather than identifying resilient individuals, we encourage building more complete models of cognition to better identify the specific adverse and protective factors that influence cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Clinical effectiveness of coronavirus disease 2019 (COVID‐19) vaccination in solid organ transplant recipients (SOTRs) is not well documented despite multiple studies demonstrating sub‐optimal immunogenicity. Methods: We reviewed medical records of eligible SOTRs at a single center to assess vaccination status and identify cases of symptomatic COVID‐19 from January 1 to August 12, 2021. We developed a Cox proportional hazards model using the date of vaccination and time since transplantation as a time‐varying covariate with age and gender as potential time‐invariant confounders. Survival curves were created using the parameters estimated from the Cox model. Results: Among 1904 SOTRs, 1362 were fully vaccinated (96% received mRNA vaccines) and 542 were either unvaccinated (n = 470) or partially vaccinated (n = 72). There were 115 cases of COVID‐19, of which 12 occurred in fully vaccinated individuals. Cox regression with the date of vaccination and time since transplantation as the time‐varying co‐variates showed that after baseline adjustment for age and sex, being fully vaccinated had a significantly lower hazard for COVID‐19, hazard ratio (HR) = 0.29 and 95% confidence interval ([CI] 0.09, 0.91). Conclusion: We found that 2‐dose mRNA COVID‐19 vaccination was protective of symptomatic COVID‐19 in vaccinated versus unvaccinated SOTRs. Tweet: COVID‐19 vaccination was associated with a significantly lower hazard for symptomatic COVID‐19 (HR 0.29; 95% CI 0.09, 0.91) among 1904 SOT recipients at a single center from January 1 to August 12, 2021. [ABSTRACT FROM AUTHOR]

Cognitive change in people with schizophrenia (PwS) is challenging to assess, but important to understand. Previous studies with limited age ranges and follow-up were subject to practice effects. Controlling for practice effects in a well-established cohort, we examined executive functioning trajectories and their association with inflammatory biomarkers, hypothesizing that PwS will have worsening executive functioning over time compared to non-psychiatric comparison participants (NCs), predicted by higher baseline inflammation with a stronger relationship in PwS than NCs. Executive functioning was assessed in 350 participants (n = 186 PwS, 164 NCs) at 12–16-month intervals (0 to 7 follow-up visits). Inflammatory biomarkers at baseline included high sensitivity C-Reactive Protein (hs-CRP), Interferon-gamma, Tumor Necrosis Factor (TNF)-alpha, and Interleukin(IL)-6, −8, and − 10. Executive functioning trajectories across diagnostic groups were estimated using a linear mixed-effects model controlling for age, sex, race/ethnicity, and education level, with additional models to assess prediction by baseline inflammation. Over 4.4 years average follow-up, improvements in executive functioning were attenuated in PwS and older participants. Controlling for practice effects negated improvements, revealing declines among highly educated participants regardless of diagnosis. Higher baseline hs-CRP predicted worse executive functioning only among NCs, while TNF-alpha was predictive of change in all participants only after controlling for practice effects. Only the main effect of hs-CRP on executive function was significant after adjusting for multiple comparisons. None of the other inflammatory biomarkers predicted executive functioning or trajectories of performance among study participants. Systemic inflammation as reflected by baseline inflammatory biomarker levels did not predict longitudinal declines in executive functioning. Additional studies examining the temporal dynamics of inflammation and cognition in PwS will help further clarify their relationship and associated mechanisms. • Higher baseline TNF-alpha predicted worse cognition over 4.4 years, but not after controlling for multiple comparisons. • After controlling for practice effects, people with schizophrenia did not have accelerated decline in executive functioning. • Older age and less education were associated with worse cognitive functioning. [ABSTRACT FROM AUTHOR]

• A lifestyle composite of smoking, alcohol consumption, diet, physical activity, and social engagement at age 40 was associated with accelerated brain aging in old age. • Brain aging and AD-brain signature in old age were worse among participants with lower age 20 cognitive ability. • Lower cognitive ability predicted better brain outcomes if lifestyle was favorable, but high cognitive ability predicted better brain outcomes regardless of lifestyle. • Favorable early midlife lifestyle may be protective against neurodegeneration and dementia risk especially among adults with lower cognitive ability. • Efforts at prevention could be prioritized earlier in midlife. We examined the influence of lifestyle on brain aging after nearly 30 years, and tested the hypothesis that young adult general cognitive ability (GCA) would moderate these effects. In the community-dwelling Vietnam Era Twin Study of Aging (VETSA), 431 largely non-Hispanic white men completed a test of GCA at mean age 20. We created a modifiable lifestyle behavior composite from data collected at mean age 40. During VETSA, MRI-based measures at mean age 68 included predicted brain age difference (PBAD), Alzheimer's disease (AD) brain signature, and abnormal white matter scores. There were significant main effects of young adult GCA and lifestyle on PBAD and the AD signature (p s ≤ 0.012), and a GCA-by-lifestyle interaction on both (p s ≤ 0.006). Regardless of GCA level, having more favorable lifestyle behaviors predicted less advanced brain age and less AD-like brain aging. Unfavorable lifestyles predicted advanced brain aging in those with lower age 20 GCA, but did not affect brain aging in those with higher age 20 GCA. Targeting early lifestyle modification may promote dementia risk reduction, especially among lower reserve individuals. [ABSTRACT FROM AUTHOR]

Abstract: Aims: This paper is aimed to develop and validate the hypertension scale of the system of Quality of Life Instruments for Chronic Diseases, QLICD-HY. Methods: The QLICD-HY instrument was developed based on programmed decision procedures with multiple nominal and focus group discussions and pilot testing. A total of 157 inpatients with hypertension were used to provide the data measuring QOL three times before and after treatment. The psychometric properties of the scale were evaluated with respect to validity, reliability and responsiveness employing correlation and factor analyses, and t-tests. Results: Correlation and factor analyses confirmed good construct validity and criterion-related validity when using Short Form (36) Health Survey (SF-36) as a criterion. Test–retest reliability coefficients (Pearson r and intra-class correlation (ICC)) for the overall instrument score and all domains except for the hypertension-specific domain (SPD) (0.75) were higher than 0.80 with a range of 0.75–0.91; the internal consistency α for all domains except for the hypertension-specific domain (0.66) was higher than 0.70. The overall score and scores for most facets within each domain except for the social domain (SOD) had statistically significant changes (t-tests) after treatment with moderate effect sizes. Conclusion: QLICD-HY has good validity, reliability, responsiveness and can be used as the quality-of-life instrument for patients with hypertension. [Copyright &y& Elsevier]

Assay sensitivity has been proposed as a criterion for including psychiatric clinical outcome studies in meta-analyses. The authors assess the performance of assay sensitivity as a method for determining study appropriateness for meta-analysis by calculating expected standard drug vs placebo effect sizes for various combinations of high quality and flawed studies. In the absence of flawed studies, expected effect sizes are close to unbiased only when sample sizes are very large. In the presence of flawed studies, expected effect sizes tend to be substantially biased except under simultaneous conditions of high power, a large proportion of flawed studies, and a population standard vs placebo effect size of flawed studies considerably lower than that of high quality studies. The authors conclude that this method is not robust and can lead to serious bias. Unless it can be shown that specific conditions hold, assay sensitivity should not be used to make quality judgments of studies. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Less acculturated Chinese Americans experience cultural and language barriers. The present study assessed the relationship between linguistic aspects of acculturation and cigarette smoking among Chinese Americans. A cross-sectional, self-administered survey was administered to a consecutive sample of 541 Chinese American adults (aged 18 years or older) attending four pediatric, medical, or dental practices located in Philadelphia's Chinatown from November 2000 to February 2001. Linguistic acculturation was measured by adapting a reliable and valid acculturation scale developed for Southeast Asians. English and Chinese language proficiency subscales were utilized to analyze the association between language proficiency and current smoking. Whereas 25% of Chinese American men reported current smoking, only 3% of Chinese American women reported current smoking. Chinese American men with lower English proficiency reported significantly higher rates of current smoking compared with Chinese American men with a higher level of English proficiency (33% vs. 18%, p <.01). Less English-proficient Chinese American male smokers were less likely to have received advice from a physician to quit smoking (50% vs. 85%, p =.01). In multivariate analysis, increased English proficiency was associated with decreased odds of current smoking ( OR =0.38, 95% CI =0.16-0.89) among Chinese American men after controlling for confounding variables. In conclusion, higher English proficiency was associated with decreased current smoking among Chinese American men. Chinese American men with limited English proficiency should especially be targeted for tobacco control interventions. Further research is needed to assess whether acculturation is associated with smoking among Chinese American women and with use of smoking cessation treatments and services by Chinese American smokers. [ABSTRACT FROM AUTHOR]

Statistical methods for analysis of survey data have been developed to facilitate research. More recently, Lumley and Scott (2013) developed an approach to extend the Mann‐Whitney‐Wilcoxon (MWW) rank sum test to survey data. Their approach focuses on the null of equal distribution. In many studies, the MWW test is called for when two‐sample t‐tests (with or without equal variance assumed) fail to provide meaningful results, as they are highly sensitive to outliers. In such situations, the null of equal distribution is too restrictive, as interest lies in comparing centers of groups. In this article, we develop an approach to extend the MWW test to survey data to test the null of equal mean rank. Although not as popular as the mean and median, the mean rank is also a meaningful measure of the center of a distribution and is the same as the median for a symmetric distribution. We illustrate the proposed approach and show major differences with Lumley and Scott's alternative using both real and simulated data. [ABSTRACT FROM AUTHOR]

Wisdom has gained increasing interest among researchers as a personality trait relevant to well-being and mental health. We previously reported development of a new 24-item San Diego Wisdom Scale (SD-WISE), with good to excellent psychometric properties, comprised of six subscales: pro-social behaviors, emotional regulation, self-reflection (insight), tolerance for divergent values (acceptance of uncertainty), decisiveness, and social advising. There is controversy about whether spirituality is a marker of wisdom. The present cross-sectional study sought to address that question by developing a new SD-WISE subscale of spirituality and examining its associations with various relevant measures. Data were collected from a national-level sample of 1,786 community-dwelling adults age 20–82 years, as part of an Amazon M-Turk cohort. Participants completed the 24-item SD-WISE along with several subscales of a commonly used Brief Multidimensional Measure of Religiousness/Spirituality, along with validated scales for well-being, resilience, happiness, depression, anxiety, loneliness, and social network. Using latent variable models, we developed a Spirituality subscale, which demonstrated acceptable psychometric properties including a unidimensional factor structure and good reliability. Spirituality correlated positively with age and was higher in women than in men. The expanded 28-item, 7-subscale SD-WISE total score (called the Jeste-Thomas Wisdom Index or JTWI) demonstrated acceptable psychometric properties. The Spirituality subscale was positively correlated with good mental health and well-being, and negatively correlated with poor mental health. However, compared to other components of wisdom, the Spirituality factor showed weaker (i.e., small-to-medium vs. medium-to-large) association with the SD-WISE higher-order Wisdom factor (JTWI). Similar to other components as well as overall wisdom, spirituality is significantly associated with better mental health and well-being, and may add to the predictive utility of the total wisdom score. Spirituality is, however, a weaker contributor to overall wisdom than components like pro-social behaviors and emotional regulation. Longitudinal studies of larger and more diverse samples are needed to explore mediation effects of these constructs on well-being and health. [ABSTRACT FROM AUTHOR]

Objective: Heavy alcohol consumption is associated with poorer cognitive function in older adults. Although understudied in middle-aged adults, the relationship between alcohol and cognition may also be influenced by genetics such as the apolipoprotein (ApoE) ε4 allele, a risk factor for Alzheimer's disease. We examined the relationship between alcohol consumption, ApoE genotype, and cognition in middle-aged adults and hypothesized that light and/or moderate drinkers (≤2 drinks per day) would show better cognitive performance than heavy drinkers or non-drinkers. Additionally, we hypothesized that the association between alcohol use and cognitive function would differ by ApoE genotype (ε4+ vs. ε4−). Method: Participants were 1266 men from the Vietnam Era Twin Study of Aging (VETSA; M age = 56; range 51–60) who completed a neuropsychological battery assessing seven cognitive abilities: general cognitive ability (GCA), episodic memory, processing speed, executive function, abstract reasoning, verbal fluency, and visuospatial ability. Alcohol consumption was categorized into five groups: never, former, light, moderate, and heavy. Results: In fully adjusted models, there was no significant main effect of alcohol consumption on cognitive functions. However, there was a significant interaction between alcohol consumption and ApoE ε4 status for GCA and episodic memory, such that the relationship of alcohol consumption and cognition was stronger in ε4 carriers. The ε4+ heavy drinking subgroup had the poorest GCA and episodic memory. Conclusions: Presence of the ε4 allele may increase vulnerability to the deleterious effects of heavy alcohol consumption. Beneficial effects of light or moderate alcohol consumption were not observed. [ABSTRACT FROM AUTHOR]

• Fecal levels of C. albicans and ECE1 are increased in patients with alcoholic hepatitis. • Candidalysin enhances ethanol-induced liver disease and is associated with higher mortality in mice. • Candidalysin damages hepatocytes in a dose-dependent manner. • Candidalysin is associated with the severity of liver disease and mortality in patients with alcoholic hepatitis. Alcohol-associated liver disease is a leading indication for liver transplantation and a leading cause of mortality. Alterations to the gut microbiota contribute to the pathogenesis of alcohol-associated liver disease. Patients with alcohol-associated liver disease have increased proportions of Candida spp. in the fecal mycobiome, yet little is known about the effect of intestinal Candida on the disease. Herein, we evaluated the contributions of Candida albicans and its exotoxin candidalysin in alcohol-associated liver disease. C. albicans and the extent of cell elongation 1 (ECE1) were analyzed in fecal samples from controls, patients with alcohol use disorder and those with alcoholic hepatitis. Mice colonized with different and genetically manipulated C. albicans strains were subjected to the chronic-plus-binge ethanol diet model. Primary hepatocytes were isolated and incubated with candidalysin. The percentages of individuals carrying ECE1 were 0%, 4.76% and 30.77% in non-alcoholic controls, patients with alcohol use disorder and patients with alcoholic hepatitis, respectively. Candidalysin exacerbates ethanol-induced liver disease and is associated with increased mortality in mice. Candidalysin enhances ethanol-induced liver disease independently of the β-glucan receptor C-type lectin domain family 7 member A (CLEC7A) on bone marrow-derived cells, and candidalysin does not alter gut barrier function. Candidalysin can damage primary hepatocytes in a dose-dependent manner in vitro and is associated with liver disease severity and mortality in patients with alcoholic hepatitis. Candidalysin is associated with the progression of ethanol-induced liver disease in preclinical models and worse clinical outcomes in patients with alcoholic hepatitis. Candidalysin is a peptide toxin secreted by the commensal gut fungus Candida albicans. Candidalysin enhances alcohol-associated liver disease independently of the β-glucan receptor CLEC7A on bone marrow-derived cells in mice without affecting intestinal permeability. Candidalysin is cytotoxic to primary hepatocytes, indicating a direct role of candidalysin on ethanol-induced liver disease. Candidalysin might be an effective target for therapy in patients with alcohol-associated liver disease. [ABSTRACT FROM AUTHOR]

Persons with schizophrenia and schizoaffective disorder (PwS) have high rates of cardiometabolic pathology that contributes to premature mortality. Adiponectin is a metabolic hormone affecting insulin sensitivity and inflammation, and is active in the brain. High-molecular weight (HMW) adiponectin is considered a more sensitive marker of metabolic dysfunction than total adiponectin, but has been poorly studied in schizophrenia. This was a cross-sectional study of 100 PwS, age range 26–68 years (46 women), and 93 age- and sex-comparable non-psychiatric comparison (NC) subjects. Assessments included measures of psychopathology, physical health, cognitive function, and circulating biomarkers of metabolic dysfunction (HMW adiponectin, lipids, insulin resistance) and inflammation (high-sensitivity C-reactive protein or hs-CRP, Tumor Necrosis Factor-α, Interleukin-6, and Interleukin-10). HMW adiponectin levels were lower in PwS compared to NCs. Lower HMW adiponectin levels were associated with higher body mass index (BMI), higher Framingham risk for coronary heart disease, higher number of metabolic syndrome criteria, greater insulin resistance, lower HDL cholesterol, and higher hs-CRP in both groups. Only in PwS, lower HMW adiponectin correlated with younger age. In the best-fit regression models of HMW adiponectin, lower levels were associated with lower HDL cholesterol and minority race/ethnicity in both groups; but with younger age, non-smoking, higher insulin resistance, and a diagnosis of schizoaffective disorder only among PwS, and with male sex, better cognitive functioning, and higher hs-CRP levels in NCs only. HMW adiponectin may be a promising biomarker of cardiometabolic health, especially among PwS. Adiponectin is a potential target for lifestyle and pharmacological interventions. Research on the possible role of HMW adiponectin in modifying cardiometabolic pathology in schizophrenia is needed. • High-molecular weight adiponectin is understudied in schizophrenia. • Schizophrenia patients have lower adiponectin levels than non-psychiatric controls. • Adiponectin may be a promising biomarker of cardio-metabolic health in schizophrenia. [ABSTRACT FROM AUTHOR]

Recent decades have seen growing empirical research in wisdom as a complex, trait-based psychological characteristic. Wisdom has been shown to possess individual and societal benefits through associations with health and well-being, but it has not yet been evaluated in people with schizophrenia (PwS). In the current study, we administered a widely used, validated 3-dimensional wisdom scale that includes three interrelated dimensions: cognitive, reflective, and affective. We examined group differences in wisdom, as well as relationships between wisdom and sociodemographics, clinical symptoms, neurocognitive and functional performance, and mental and physical health in 65 stable adult outpatients with chronic schizophrenia or schizoaffective disorder and 96 non-psychiatric comparison participants (NPCPs). Results showed that PwS had lower wisdom scores than NPCPs and that wisdom moderated relationships between diagnostic group and neurocognitive and functional performance; PwS with higher levels of wisdom demonstrated better cognitive performance than did PwS with lower levels of wisdom. In addition, wisdom was positively correlated with performances on multiple neurocognitive tasks in PwS, but not in NPCPs. Finally, reflective wisdom - representing accurate/unbiased introspection and perspective-taking - correlated with all mental health variables in PwS. Our results were limited by a cross-sectional design, but suggest that wisdom, especially reflective wisdom, may be associated with better cognitive performance and better physical and mental health in PwS. It is conceivable that interventions to enhance wisdom may have broad cognitive and mental and physical health benefits in individuals with chronic psychotic disorders. [ABSTRACT FROM AUTHOR]

The p value has been widely used as a way to summarise the significance in data analysis. However, misuse and misinterpretation of the p value is common in practice. Our result shows that if the model specification is wrong, the distribution of the p value may be inappropriate, which makes the decision based on the p value invalid. [ABSTRACT FROM AUTHOR]

• Non-medical residential care facilities (RCFs) house many people with schizophrenia. • However the impact of RCFs on mental/physical health and well-being is unclear. • RCF residents have a few worse prognostic indicators and lower HDL levels. • Yet RCF residents have better mental health and comparable physical health. • Biomarkers of aging (metabolic and inflammatory function) were comparable as well. This paper aims to compare mental and physical health, cognitive functioning, and selected biomarkers of aging reflecting metabolic pathology and inflammation, in outpatients with schizophrenia from two residential settings: residential care facilities (RCFs) and living with someone in a house/apartment. This cross-sectional study examined community-dwelling adults with schizophrenia either in RCFs (N = 100) or in a house/apartment with someone (N = 76), recruited for two NIH-funded studies in San Diego. Assessments included measures of mental/physical health, cognitive function, and metabolic (glycosylated hemoglobin, cholesterol) and inflammatory (C-Reactive Protein, Tumor Necrosis Factor-alpha, Interleukin-6) biomarkers of aging. General logistic models were used to analyze factors associated with residential status. RCF residents had several indicators of worse prognosis (never being married, higher daily antipsychotic dosages, increased comorbidities and higher Framingham risk for coronary heart disease) than individuals living with someone. However, RCF residents had better mental well-being and lower BMI, as well as comparable biomarkers of aging as those living with someone. While the cross-sectional nature of the study does not allow us to infer causality, it is possible that the supportive environment of RCFs may have a positive impact on mental and physical health of persons with schizophrenia. Longitudinal follow-up studies are needed to test this hypothesis. [ABSTRACT FROM AUTHOR]

How and when education improves cognitive capacity is an issue of profound societal importance. Education and later-life educationrelated factors, such as occupational complexity and engagement in cognitive-intellectual activities, are frequently considered indices of cognitive reserve, but whether their effects are truly causal remains unclear. In this study, after accounting for general cognitive ability (GCA) at an average age of 20 y, additional education, occupational complexity, or engagement in cognitive-intellectual activities accounted for little variance in late midlife cognitive functioning in men age 56-66 (n= 1009). Age 20 GCA accounted for 40% of variance in the same measure in late midlife and approximately 10% of variance in each of seven cognitive domains. The other factors each accounted for <1% of the variance in cognitive outcomes. The impact of these other factors likely reflects reverse causation--namely, downstream effects of early adult GCA. Supporting that idea, age 20 GCA, but not education, was associated with late midlife cortical surface area (n = 367). In our view, the most parsimonious explanation of our results, a meta-analysis of the impact of education, and epidemiologic studies of the Flynn effect is that intellectual capacity gains due to education plateau in late adolescence/early adulthood. Longitudinal studies with multiple cognitive assessments before completion of education would be needed to confirm this speculation. If cognitive gains reach an asymptote by early adulthood, then strengthening cognitive reserve and reducing later-life cognitive decline and dementia risk may really begin with improving educational quality and access in childhood and adolescence. [ABSTRACT FROM AUTHOR]

Large-scale public health prevention initiatives and interventions are a very important component to current public health strategies. But evaluating effects of such large-scale prevention/intervention faces a lot of challenges due to confounding effects and heterogeneity of study population. In this paper, we will develop metrics to assess the risk for suicide events based on causal inference framework when the study population is heterogeneous. The proposed metrics deal with the confounding effect by first estimating the risk of suicide events within each of the risk levels, number of prior attempts, and then taking a weighted sum of the conditional probabilities. The metrics provide unbiased estimates of the risk of suicide events. Simulation studies and a real data example will be used to demonstrate the proposed metrics. [ABSTRACT FROM AUTHOR]

SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC SURVEYLOGISTIC to facilitate analysis of data from complex survey studies. On the other hand, PROC MEANS and many other classic SAS procedures also provide an option for including weights and yield identical point estimates, but different standard errors (SEs), as their corresponding survey procedures. This paper takes an in-depth look at different types of weights and provides guidance on use of different SAS procedures. [ABSTRACT FROM AUTHOR]

Background: Insomnia is common in service members and associated with many mental and physical health problems. Recently, longitudinal data have been used to assess the impact of disturbed sleep on mental health outcomes. These studies have consistently shown relationships between sleep disturbance and development of mental illness. Objective: The present study examined the longitudinal relationship between sleep disturbance and PTSD symptomatology in a cohort of Marines and Navy Corpsmen deployed to Iraq and Afghanistan (n = 2,404) assessed prior to deployment, as well as at −3 and 6 months post-deployment. Additionally, we aimed to investigate the extent to which these relationships are moderated by combat-stress severity, and to what extent these findings are replicated in a second, separate cohort of Marines and Navy corpsmen (n = 938) assessed with identical measures prior to deployment and within 3 months of return. Method: The present study employed latent variable path models to examine the relationships between pre-deployment sleep disturbance and post-deployment re-experiencing symptoms. Initial cross-lagged path models were conducted on discovery and replication samples to validate the hypothesized predictive relationships. Follow up moderation path models were then conducted to include the effect of combat-stress severity on these relationships. Results: Initial cross-lagged models supported a significant relationship between pre-deployment sleep disturbance and future re-experiencing PTSD symptoms at all time points. Initial moderation models showed a small moderator effect of combat-stress severity, though the main predictive relationship between pre-deployment sleep disturbance and PTSD symptoms remained significant. The moderator effect was not significant in the replication sample. Conclusions: The results of this study support pre-deployment sleep disturbance as a risk factor for development of post-deployment PTSD symptoms. Interventions aimed at normalizing sleep may be important in preventive measures for PTSD. [ABSTRACT FROM AUTHOR]

Objectives: A recently published simulation study suggested that women are inferior leaders of cardiopulmonary resuscitation efforts. The aim of this study was to compare female and male code leaders in regard to cardiopulmonary resuscitation outcomes in a real-world clinical setting.Design: Retrospective cohort review.Setting: Two academic, urban hospitals in San Diego, California.Subjects: One-thousand eighty-two adult inpatients who suffered cardiac arrest and underwent cardiopulmonary resuscitation.Interventions: None.Measurements and Main Results: We analyzed whether physician code leader gender was independently associated with sustained return of spontaneous circulation and survival to discharge and with markers of quality cardiopulmonary resuscitation. Of all arrests, 327 (30.1%) were run by female physician code leaders with 251 (76.8%) obtaining return of spontaneous circulation, and 122 (37.3%) surviving to discharge. Male physicians ran 757 codes obtaining return of spontaneous circulation in 543 (71.7%) with 226 (29.9%) surviving to discharge. When adjusting for variables, female physician code leader gender was independently associated with a higher likelihood of return of spontaneous circulation (odds ratio, 1.36; 95% CI, 1.01-1.85; p = 0.049) and survival to discharge (odds ratio, 1.53; 95% CI, 1.15-2.02; p < 0.01). Additionally, the odds ratio for survival to discharge was 1.62 (95% CI, 1.13-2.34; p < 0.01) for female physicians with a female code nurse when compared with male physician code leaders paired with a female code nurse. Gender of code leader was not associated with cardiopulmonary resuscitation quality.Conclusions: In contrast to data derived from a simulated setting with medical students, real life female physician leadership of cardiopulmonary resuscitation is not associated with inferior outcomes. Appropriately, trained physicians can lead high-quality cardiopulmonary resuscitation irrespective of gender. [ABSTRACT FROM AUTHOR]

The first probabilistic definition of the geometric mean of a non negative random variable under certain assumptions was given in Feng et al. (2013). In this paper, we generalize the definition to a larger class of random variables. We also show the basic properties of the geometric mean and point out its discontinuity and instability. Some convergence properties are studied as well, for which we emphasize its link to the positive moments of the random variable. A discussion of potential applications of the new definition in biomedical research and open questions to complete the theory of geometric mean is highlighted. [ABSTRACT FROM PUBLISHER]

Andersen's plot, a graphical method for testing the proportionality assumption in the Cox Regression Model (Cox, 1972), first proposed by Kay (1977) and popularized by Andersen (1982), has been used widely in biomedical research to check the validity of applying this popular regression model in survival analysis. Our theoretical derivation and examples show that the theoretical basis of this method is flawed. The graphical method should not be used in testing the proportionality. Instead, formal analytical methods based on residuals such as Cox–Snell residual and martingale residual should be used in practice. [ABSTRACT FROM PUBLISHER]

Mean-based semi-parametric regression models such as the popular generalized estimating equations are widely used to improve robustness of inference over parametric models. Unfortunately, such models are quite sensitive to outlying observations. The Wilcoxon-score-based rank regression (RR) provides more robust estimates over generalized estimating equations against outliers. However, the RR and its extensions do not sufficiently address missing data arising in longitudinal studies. In this paper, we propose a new approach to address outliers under a different framework based on the functional response models. This functional-response-model-based alternative not only addresses limitations of the RR and its extensions for longitudinal data, but, with its rank-preserving property, even provides more robust estimates than these alternatives. The proposed approach is illustrated with both real and simulated data. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Campaigns have become popular in public health approaches to suicide prevention; however, limited empirical investigation of their impact on behavior has been conducted. To address this gap, utilization patterns of crisis support services associated with the Department of Veterans Affairs' Veterans Crisis Line (VCL) suicide prevention campaign were examined. Daily call data for the National Suicide Prevention Lifeline, VCL, and 1-800-SUICIDE were modeled using a novel semi-varying coefficient method. Analyses reveal significant increases in call volume to both targeted and broad resources during the campaign. Findings underscore the need for further research to refine measurement of the effects of these suicide prevention efforts. [ABSTRACT FROM AUTHOR]

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We tested hypotheses that greater connectedness to parent(s) is associated with lower risk for nonlethal suicidal thoughts and behavior (STB), termed direct protective effects, and that parent connectedness serves to moderate (lower) the risk for STB associated with psychopathology including major depressive episode (MDE), termed moderating protective effects. Independent samples of children and adolescents recruited for a multicenter study of familial alcoholism were studied. Generalized estimating equation models were used that adjusted for age, sex, and youth psychopathology variables. The sample for Study 1 was assessed at baseline and about 2- and 4-year follow-ups, with baseline characteristics ofn = 921,Mage = 14.3 ± 1.8 years, and 51.8% female. The sample for Study 2 was assessed at baseline and about 5-year follow-up, with baseline characteristics ofn = 867,Mage = 12.0 ± 3.2 years, and 51.0% female. In both studies, increased perceived connectedness to father but not mother was associated with lower risk for measures of STB, consistent with direct protective effects. In Study 1, measures of parent connectedness were associated with lower risk for STB but only for youth that did not experience MDE (or alcohol use disorder), inconsistent with moderating protective effects. Study 2 showed that connectedness to fathers was associated with lower risk for suicide plans or attempts (severe STB) but not frequent thoughts of death or dying (nonsevere STB). Improved connectedness to fathers may lower risk for STB in children and adolescents, consistent with direct protective effects. Hypotheses about moderating protective effects were not supported. [ABSTRACT FROM PUBLISHER]

The relative risk, risk difference, and odds ratio are the three most commonly used measures for comparing the risk of disease between different groups. Although widely popular in biomedical and psychosocial research, the relationship among the three measures has not been clarified in the literature. Many researchers incorrectly assume a monotonic relationship, such that higher (or lower) values in one measure are associated with higher (or lower) values in the other measures. In this paper we discuss three theorems and provide examples demonstrating that this is not the case; there is no logical relationship between any of these measures. Researchers must be very cautious when implying a relationship between the different measures or when combining results of studies that use different measures of risk. [ABSTRACT FROM AUTHOR]

Zero-inflated Poisson (ZIP) and negative binomial (ZINB) models are widely used to model zero-inflated count responses. These models extend the Poisson and negative binomial (NB) to address excessive zeros in the count response. By adding a degenerate distribution centered at 0 and interpreting it as describing a non-risk group in the population, the ZIP (ZINB) models a two-component population mixture. As in applications of Poisson and NB, the key difference between ZIP and ZINB is the allowance for overdispersion by the ZINB in its NB component in modeling the count response for the at-risk group. Overdispersion arising in practice too often does not follow the NB, and applications of ZINB to such data yield invalid inference. If sources of overdispersion are known, other parametric models may be used to directly model the overdispersion. Such models too are subject to assumed distributions. Further, this approach may not be applicable if information about the sources of overdispersion is unavailable. In this paper, we propose a distribution-free alternative and compare its performance with these popular parametric models as well as a moment-based approach proposed by Yu et al. [Statistics in Medicine 2013; 32: 2390-2405]. Like the generalized estimating equations, the proposed approach requires no elaborate distribution assumptions. Compared with the approach of Yu et al., it is more robust to overdispersed zero-inflated responses. We illustrate our approach with both simulated and real study data. [ABSTRACT FROM AUTHOR]

In this article, we compare the zero-inflated Poisson (ZIP) and negative binomial (NB) distributions based on three most important criteria: the probability of zero, the mean value, and the variance. Our results show that with same mean value and variance, the ZIP distribution always has a larger probability of zeros; with same mean value and probability of zeros, the NB distribution always has a larger variance; and with same variance and probability of zeros, the ZIP distribution always has a larger mean value. We also study the properties of Vuong test in model selection in three cases by simulations. [ABSTRACT FROM PUBLISHER]

Background: The compression of morbidity model posits a breakpoint in the adult lifespan that separates an initial period of relative health from a subsequent period of ever increasing morbidity. Researchers often assume that such a breakpoint exists; however, this assumption is hitherto untested. Purpose: To test the assumption that a breakpoint exists—which we term a morbidity tipping point—separating a period of relative health from a subsequent deterioration in health status. An analogous tipping point for healthcare costs was also investigated. Methods: Four years of adults’ (N = 55,550) morbidity and costs data were retrospectively analyzed. Data were collected in Pittsburgh, PA between 2006 and 2009; analyses were performed in Rochester, NY and Ann Arbor, MI in 2012 and 2013. Cohort-sequential and hockey stick regression models were used to characterize long-term trajectories and tipping points, respectively, for both morbidity and costs. Results: Morbidity increased exponentially with age (P<.001). A morbidity tipping point was observed at age 45.5 (95% CI, 41.3-49.7). An exponential trajectory was also observed for costs (P<.001), with a costs tipping point occurring at age 39.5 (95% CI, 32.4-46.6). Following their respective tipping points, both morbidity and costs increased substantially (Ps<.001). Conclusions: Findings support the existence of a morbidity tipping point, confirming an important but untested assumption. This tipping point, however, may occur earlier in the lifespan than is widely assumed. An “avalanche of morbidity” occurred after the morbidity tipping point—an ever increasing rate of morbidity progression. For costs, an analogous tipping point and “avalanche” were observed. The time point at which costs began to increase substantially occurred approximately 6 years before health status began to deteriorate. [ABSTRACT FROM AUTHOR]

Estimating causal treatment effect for randomized controlled trials under post-treatment confounding, that is, noncompliance and informative dropouts, is becoming an important problem in intervention/prevention studies when the treatment exposures are not completely controlled. When confounding is present in a study, the traditional intention-to-treat approach could underestimate the treatment effect because of insufficient exposure of treatment. In the recent two decades, many papers have been published to address such confounders to investigate the causal relationship between treatment and outcome of interest based on different modeling strategies. Most of the existing approaches, however, are suitable only for standard experiments. In this paper, we propose a new class of structural functional response model to address post-treatment confounding in complex multi-layered intervention studies within a longitudinal data setting. The new approach offers robust inference and is readily implemented. We illustrate and assess the performance of the proposed structural functional response model using both real and simulated data. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The log-transformation is widely used in biomedical and psychosocial research to deal with skewed data. This paper highlights serious problems in this classic approach for dealing with skewed data. Despite the common belief that the log transformation can decrease the variability of data and make data conform more closely to the normal distribution, this is usually not the case. Moreover, the results of standard statistical tests performed on log-transformed data are often not relevant for the original, non-transformed data. We demonstrate these problems by presenting examples that use simulated data. We conclude that if used at all, data transformations must be applied very cautiously. We recommend that in most circumstances researchers abandon these traditional methods of dealing with skewed data and, instead, use newer analytic methods that are not dependent on the distribution the data, such as generalized estimating equations (GEE). [ABSTRACT FROM AUTHOR]

The log transformation has been widely used in biomedical research to deal with the skewed data. However, in the medical publications, we have found many misuses and misinterpretations of analysis based on log-transformed data. In this paper, we list some common scenarios of misuse and misinterpretation of log transformation in biomedical applications. We also provide both theoretical and practical justifications to support our viewpoints. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]