Introduction: The replication crisis in the behavioral and social sciences spawned a credibility revolution, calling for new open science research practices that ensure greater transparency, including preregistrations, open data and code, and open access. Statement of the Problem: Replications of published research are an important element in this…

Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…

Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…

Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…

Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…

Confidence intervals (CIs) for parameters are usually constructed based on the estimated standard errors. These are known as Wald CIs. This article argues that likelihood-based CIs (CIs based on likelihood ratio statistics) are often preferred to Wald CIs. It shows how the likelihood-based CIs and the Wald CIs for many statistics and psychometric…

An obstacle to broader acceptability of effect sizes in single case research is their lack of intuitive and useful interpretations. Interpreting Cohen's d as "standard deviation units difference" and R[superscript 2] as "percent of variance accounted for" do not resound with most visual analysts. In fact, the only comparative analysis widely…

The standardized group mean difference, Cohen's "d", is among the most commonly used and intuitively appealing effect sizes for group comparisons. However, reporting this point estimate alone does not reflect the extent to which sampling error may have led to an obtained value. A confidence interval expresses the uncertainty that exists between…

In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…