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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
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Timmerman, Marieke E.; Lorenzo-Seva, Urbano – Psychological Methods, 2011
Parallel analysis (PA) is an often-recommended approach for assessment of the dimensionality of a variable set. PA is known in different variants, which may yield different dimensionality indications. In this article, the authors considered the most appropriate PA procedure to assess the number of common factors underlying ordered polytomously…
Descriptors: Statistical Analysis, Factor Analysis, Correlation
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Smith, Justin D. – Psychological Methods, 2012
This article systematically reviews the research design and methodological characteristics of single-case experimental design (SCED) research published in peer-reviewed journals between 2000 and 2010. SCEDs provide researchers with a flexible and viable alternative to group designs with large sample sizes. However, methodological challenges have…
Descriptors: Research Design, Research Methodology, Psychological Studies, Journal Articles
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Coffman, Donna L.; Zhong, Wei – Psychological Methods, 2012
This article presents marginal structural models with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW…
Descriptors: Mediation Theory, Statistical Analysis, Causal Models, Computation
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Baldwin, Scott A.; Bauer, Daniel J.; Stice, Eric; Rohde, Paul – Psychological Methods, 2011
Partially clustered designs, where clustering occurs in some conditions and not others, are common in psychology, particularly in prevention and intervention trials. This article reports results from a simulation comparing 5 approaches to analyzing partially clustered data, including Type I errors, parameter bias, efficiency, and power. Results…
Descriptors: Multivariate Analysis, Error of Measurement, Statistical Analysis, Statistical Bias
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Heene, Moritz; Hilbert, Sven; Draxler, Clemens; Ziegler, Matthias; Buhner, Markus – Psychological Methods, 2011
Fit indices are widely used in order to test the model fit for structural equation models. In a highly influential study, Hu and Bentler (1999) showed that certain cutoff values for these indices could be derived, which, over time, has led to the reification of these suggested thresholds as "golden rules" for establishing the fit or other aspects…
Descriptors: Goodness of Fit, Factor Analysis, Structural Equation Models, Statistical Analysis
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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
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Bonett, Douglas G. – Psychological Methods, 2010
The conventional fixed-effects (FE) and random-effects (RE) confidence intervals that are used to assess the average alpha reliability across multiple studies have serious limitations. The FE method, which is based on a constant coefficient model, assumes equal reliability coefficients across studies and breaks down under minor violations of this…
Descriptors: Meta Analysis, Reliability, Computation, Statistical Analysis
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Manolov, Rumen; Solanas, Antonio – Psychological Methods, 2012
There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current article proposes an approach for obtaining further numerical evidence on the importance of the results,…
Descriptors: Sampling, Probability, Statistical Significance, Case Studies
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Vrieze, Scott I. – Psychological Methods, 2012
This article reviews the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) in model selection and the appraisal of psychological theory. The focus is on latent variable models, given their growing use in theory testing and construction. Theoretical statistical results in regression are discussed, and more important…
Descriptors: Factor Analysis, Statistical Analysis, Psychology, Interviews
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Bird, Kevin D. – Psychological Methods, 2011
Any set of confidence interval inferences on J - 1 linearly independent contrasts on J means, such as the two comparisons [mu][subscript 1] - [mu][subscript 2] and [mu][subscript 2] - [mu][subscript 3] on 3 means, provides a basis for the deduction of interval inferences on all other contrasts, such as the redundant comparison [mu][subscript 1] -…
Descriptors: Intervals, Statistical Analysis, Inferences, Comparative Analysis
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McGrath, Robert E.; Walters, Glenn D. – Psychological Methods, 2012
Statistical analyses investigating latent structure can be divided into those that estimate structural model parameters and those that detect the structural model type. The most basic distinction among structure types is between categorical (discrete) and dimensional (continuous) models. It is a common, and potentially misleading, practice to…
Descriptors: Factor Structure, Factor Analysis, Monte Carlo Methods, Computation
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Preacher, Kristopher J.; Zyphur, Michael J.; Zhang, Zhen – Psychological Methods, 2010
Several methods for testing mediation hypotheses with 2-level nested data have been proposed by researchers using a multilevel modeling (MLM) paradigm. However, these MLM approaches do not accommodate mediation pathways with Level-2 outcomes and may produce conflated estimates of between- and within-level components of indirect effects. Moreover,…
Descriptors: Structural Equation Models, Hypothesis Testing, Statistical Analysis, Predictor Variables
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Sterba, Sonya K.; Pek, Jolynn – Psychological Methods, 2012
Researchers in psychology are increasingly using model selection strategies to decide among competing models, rather than evaluating the fit of a given model in isolation. However, such interest in model selection outpaces an awareness that one or a few cases can have disproportionate impact on the model ranking. Though case influence on the fit…
Descriptors: Psychological Studies, Models, Selection, Statistical Analysis
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Imai, Kosuke; Keele, Luke; Tingley, Dustin – Psychological Methods, 2010
Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…
Descriptors: Structural Equation Models, Statistical Analysis, Statistical Inference, Intervention
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