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Ulrich, Rolf; Schroter, Hannes; Striegel, Heiko; Simon, Perikles – Psychological Methods, 2012
This article derives the power curves for a Wald test that can be applied to randomized response models when small prevalence rates must be assessed (e.g., detecting doping behavior among elite athletes). These curves enable the assessment of the statistical power that is associated with each model (e.g., Warner's model, crosswise model, unrelated…
Descriptors: Statistical Analysis, Models, Incidence, Sample Size
Schimmack, Ulrich – Psychological Methods, 2012
Cohen (1962) pointed out the importance of statistical power for psychology as a science, but statistical power of studies has not increased, while the number of studies in a single article has increased. It has been overlooked that multiple studies with modest power have a high probability of producing nonsignificant results because power…
Descriptors: Psychological Studies, Statistical Analysis, Probability, Statistical Significance
Lai, Keke; Kelley, Ken – Psychological Methods, 2011
In addition to evaluating a structural equation model (SEM) as a whole, often the model parameters are of interest and confidence intervals for those parameters are formed. Given a model with a good overall fit, it is entirely possible for the targeted effects of interest to have very wide confidence intervals, thus giving little information about…
Descriptors: Accuracy, Structural Equation Models, Computation, Sample Size
Bauer, Daniel J. – Psychological Methods, 2005
Measurement invariance is a necessary condition for the evaluation of factor mean differences over groups or time. This article considers the potential problems that can arise for tests of measurement invariance when the true factor-to-indicator relationship is nonlinear (quadratic) and invariant but the linear factor model is nevertheless…
Descriptors: Statistical Analysis, Sample Size, Factor Analysis, Measurement
Courvoisier, Delphine S.; Eid, Michael; Nussbeck, Fridtjof W. – Psychological Methods, 2007
Extensions of latent state-trait models for continuous observed variables to mixture latent state-trait models with and without covariates of change are presented that can separate individuals differing in their occasion-specific variability. An empirical application to the repeated measurement of mood states (N = 501) revealed that a model with 2…
Descriptors: Psychological Patterns, Simulation, Structural Equation Models, Sample Size

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