Journal ArticleDOI
Handling Item-Level Missing Data Simpler Is Just as Good
TLDR
In this article, the authors assess whether advanced methods of handling item-level missing data performed equivalently to simpler methods in designs similar to those counseling psychologists typically engage in, and support the use of available case analysis when dealing with low-level itemlevel missingness.Abstract:
The topic of missing data has been receiving increasing attention, with calls to apply advanced methods of handling missingness to counseling psychology research. The present study sought to assess whether advanced methods of handling item-level missing data performed equivalently to simpler methods in designs similar to those counseling psychologists typically engage in. Results of an initial preliminary analysis, an analysis using real-world data, and a series of simulation studies were used in the present investigation. Results indicated that available case analysis, mean substitution, and multiple imputation had similar results across low levels of missing data, though in data with higher levels of missing data and other problems (e.g., small sample size or scales with weak internal reliability) mean substitution produced inflation of correlation coefficients among items. The present results support the use of available case analysis when dealing with low-level item-level missingness.read more
Citations
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The Body Appreciation Scale-2: item refinement and psychometric evaluation.
TL;DR: The BAS-2 is a psychometrically sound positive body image measure applicable for research and clinical settings and its internal consistency, test-retest reliability, and construct (convergent, incremental, and discriminant) validity were supported.
Journal ArticleDOI
Suicidal ideation in transgender people: Gender minority stress and interpersonal theory factors.
Rylan J. Testa,Matthew S. Michaels,Whitney Bliss,Megan L. Rogers,Kimberly F. Balsam,Thomas E. Joiner +5 more
TL;DR: The models demonstrate pathways through which GMSR and IPTS constructs relate to one another and confer risk for SI among TGNC individuals and provide promising directions for future research and clinical interventions in this area.
Journal ArticleDOI
Resilience and collective action: Exploring buffers against minority stress for transgender individuals.
Aaron S. Breslow,Melanie E. Brewster,Brandon L. Velez,Stephanie N. Wong,Elizabeth Geiger,Blake Soderstrom +5 more
TL;DR: In this paper, the authors examined the relations of minority stressors (i.e., antitransgender discrimination, stigma awareness, and internalized transphobia) and individual and group-level buffers (e.g., resilience and collective action).
Journal ArticleDOI
Translation and validation of body image instruments: Challenges, good practice guidelines, and reporting recommendations for test adaptation.
Viren Swami,David Barron +1 more
TL;DR: An operational framework for conducting effective test adaptation of existing measurement tools is offered and good-practice guidelines for instrument translation and effective strategies for achieving semantic equivalence of translated instruments are suggested.
Journal ArticleDOI
Suicide risk in trans populations: An application of minority stress theory.
Elliot A. Tebbe,Bonnie Moradi +1 more
TL;DR: Findings point to minority stressors, friend support, and drug use as potentially fruitful targets of prevention and intervention efforts to reduce depression and suicide risk in trans populations.
References
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Journal Article
R: A language and environment for statistical computing.
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Journal ArticleDOI
Missing data: Our view of the state of the art.
Joseph L. Schafer,John W. Graham +1 more
TL;DR: 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI) are presented and may eventually extend the ML and MI methods that currently represent the state of the art.
Journal ArticleDOI
A Test of Missing Completely at Random for Multivariate Data with Missing Values
TL;DR: In this article, the authors proposed a global test statistic for multivariate data with missing values, that is, whether the missing data are missing completely at random (MCAR), that is whether missingness depends on the variables in the data set.
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