G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of thet, F, and χ2 test families. In addition, it includes power analyses forz tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.

https://link.springer.com/content/pdf/10.3758/BF03193146.pdf

G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

http://ibgwww.colorado.edu/cdrom2009/ScriptsA/purcell/GWAS/boulder_09_plink_intro.pdf

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

In this article the author reviews research evidence on the prevalence of mental disorders in lesbians, gay men, and bisexuals (LGBs) and shows, using meta-analyses, that LGBs have a higher prevalence of mental disorders than heterosexuals. The author offers a conceptual framework for understanding this excess in prevalence of disorder in terms of minority stress— explaining that stigma, prejudice, and discrimination create a hostile and stressful social environment that causes mental health problems. The model describes stress processes, including the experience of prejudice events, expectations of rejection, hiding and concealing, internalized homophobia, and ameliorative coping processes. This conceptual framework is the basis for the review of research evidence, suggestions for future research directions, and exploration of public policy implications. The study of mental health of lesbian, gay, and bisexual (LGB) populations has been complicated by the debate on the classification of homosexuality as a mental disorder during the 1960s and early 1970s. That debate posited a gay-affirmative perspective, which sought to declassify homosexuality, against a conservative perspective, which sought to retain the classification of homosexuality as a mental disorder (Bayer, 1981). Although the debate on classification ended in 1973 with the removal of homosexuality from the second edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM; American Psychiatric Association, 1973), its heritage has lasted. This heritage has tainted discussion on mental health of lesbians and gay men by associating— even equating— claims that LGB people have higher prevalences of mental disorders than heterosexual people with the historical antigay stance and the stigmatization of LGB persons (Bailey, 1999). However, a fresh look at the issues should make it clear that whether LGB populations have higher prevalences of mental disorders is unrelated to the classification of homosexuality as a mental disorder. A retrospective analysis would suggest that the attempt to find a scientific answer in that debate rested on flawed logic. The debated scientific question was, Is homosexuality a mental disorder? The operationalized research question that pervaded the debate was, Do homosexuals have high prevalences of mental disorders? But the research did not accurately operationalize the scientific question. The question of whether homosexuality should be considered a mental disorder is a question about classification. It can be answered by debating which behaviors, cognitions, or emotions should be considered indicators of a mental

/pdf/prejudice-social-stress-and-mental-health-in-lesbian-gay-and-2eymy1qdt5.pdf

Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence

In the context of the development of prototypic assessment instruments in the areas of cognition, personality, and adaptive functioning, the issues of standardization, norming procedures, and the important psychometrics of test reliability and validity are evaluated critically. Criteria, guidelines, and simple rules of thumb are provided to assist the clinician faced with the challenge of choosing an appropriate test instrument for a given psychological assessment. Clinicians are often faced with the critical challenge of choosing the most appropriate available test instrument for a given psychological assessment of a child, adolescent, or adult of a particular age, gender, and class of disability. It is the purpose of this report to provide some criteria, guidelines, or simple rules of thumb to aid in this complex scientific decision. As such, it draws upon my experience with issues of test development, standardization, norming procedures, and important psychometrics, namely, test reliability and validity. As I and my colleagues noted in an earlier publication, the major areas of psychological functioning, in the normal development of infants, children, adolescents, adults, and elderly people, include cognitive, academic, personality, and adaptive behaviors (Sparrow, Fletcher, & Cicchetti, 1985). As such, the major examples or applications discussed in this article derive primarily, although not exclusively, from these several areas of human functioning.

/pdf/guidelines-criteria-and-rules-of-thumb-for-evaluating-normed-ceb0hwge3w.pdf

Guidelines, Criteria, and Rules of Thumb for Evaluating Normed and Standardized Assessment Instruments in Psychology.

Two--Way Contingency Tables. Three--Way Contingency Tables. Generalized Linear Models. Logistic Regression. Loglinear Models for Contingency Tables. Building and Applying Logit and Loglinear Models. Multicategory Logit Models. Models for Matched Pairs. A Twentieth--Century Tour of Categorical Data Analysis. Appendix. Table of Chi--Squared Distribution Values for Various Right--Tail Probabilities. Bibliography. Indexes.

William A. Grove

Papers

Statistical Methods for Rates and Proportions, 2nd ed