GLIMMPSE Version 3 is a free, web-based, open-source software tool, which calculates power and sample size for general linear mixed models with Gaussian errors. The software permits power calculations for clinical trials, randomized experiments, and observational studies with clustering, repeated measures, and both, and almost any testable hypothesis. The software has been supported by five United States National Institutes of Health (NIH) grants, is used for more than 14,000 power or sample size calculations per year, has been cited in almost 500 peer-reviewed manuscripts, and used to design more than 200 million dollars in NIH-funded studies.
View Article and Find Full Text PDFThis study investigated the effect of testlets on regularization-based differential item functioning (DIF) detection in polytomous items, focusing on the generalized partial credit model with lasso penalization (GPCMlasso) DIF method. Five factors were manipulated: sample size, magnitude of testlet effect, magnitude of DIF, number of DIF items, and type of DIF-inducing covariates. Model performance was evaluated using false-positive rate (FPR) and true-positive rate (TPR).
View Article and Find Full Text PDFThe purpose of this research was to develop a short measure of technology anxiety and provide validity and reliability evidence for its use in a variety of studies in the social sciences. Technology anxiety is an emotion oriented towards a negative affect leading to the avoidance of information and communication technology (Wilson, 2018). We developed the Abbreviated Technology Anxiety Scale (ATAS) and applied measurement theory to provide validity and reliability evidence.
View Article and Find Full Text PDFThe purpose of this study was to examine the application of the multimedia and modality principles on cued-recall, recognition, and mental effort of college students with and without dyslexia. The study used a Multimedia (Image Present vs. Image Absent) × Modality (Narration vs.
View Article and Find Full Text PDFThe purpose of this design and development case is to share our experiences in the transformation of a face-to-face workshop into a Massive Open Online Course (MOOC) for a prominent MOOC platform. The goal of the workshop and MOOC is to teach learners how to conduct appropriate power and sample size analysis for multilevel and longitudinal studies in social and behavioral health research. Learners include people from across the biomedical research spectrum, from students to full professors.
View Article and Find Full Text PDFThere is a longstanding tradition in psychological research for norming lists of words that are used in experimental studies. The present study extends this practice to graphic imagery by obtaining norming data on 24 simple abstract graphic shapes composed of three straight-line segments. The attributes obtained in the norming procedure were the shapes' familiarity, describability, associability, availability, and potential for word association.
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