Factorial experimental designs have many potential advantages for behavioral scientists. For example, such designs may be useful in building more potent interventions by helping investigators to screen several candidate intervention components simultaneously and to decide which are likely to offer greater benefit before evaluating the intervention…

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

In recent years, single-case designs have increasingly been used to establish an empirical basis for evidence-based interventions and techniques in a variety of disciplines, including psychology and education. Although traditional single-case designs have typically not met the criteria for a randomized controlled trial relative to conventional…

In this article, we note the many ontological, epistemological, and methodological similarities between how Campbell and Rubin conceptualize causation. We then explore 3 differences in their written emphases about individual case matching in observational studies. We contend that (a) Campbell places greater emphasis than Rubin on the special role…

A unifying theory of subject-centered scalability is offered that is grounded in structural true score modeling, is conceptually distinct from internal consistency and homogeneity as determined by item correlations, and is empirically confirmable. Scalability holds when item true scores are perfectly correlated but differ in their individual scale…

P. R. Killeen's (2005a) probability of replication ("p[subscript rep]") of an experimental result is the fiducial Bayesian predictive probability of finding a same-sign effect in a replication of an experiment. "p[subscript rep]" is now routinely reported in "Psychological Science" and has also begun to appear in…

Calculating and reporting appropriate measures of effect size are becoming standard practice in psychological research. One of the most common scenarios encountered involves the comparison of 2 groups, which includes research designs that are experimental (e.g., random assignment to treatment vs. placebo conditions) and nonexperimental (e.g.,…

The performance of parameter estimates and standard errors in estimating F. Samejima's graded response model was examined across 324 conditions. Full information maximum likelihood (FIML) was compared with a 3-stage estimator for categorical item factor analysis (CIFA) when the unweighted least squares method was used in CIFA's third stage. CIFA…

Across many areas of psychology, concordance is commonly used to measure the (intragroup) agreement in ranking a number of items by a group of judges. Sometimes, however, the judges come from multiple groups, and in those situations, the interest is to measure the concordance between groups, under the assumption that there is some within-group…

The authors show how the use of inequality constraints on parameters in structural equation models may affect the distribution of the likelihood ratio test. Inequality constraints are implicitly used in the testing of commonly applied structural equation models, such as the common factor model, the autoregressive model, and the latent growth…

Cluster randomized trials (CRTs) have been widely used in field experiments treating a cluster of individuals as the unit of randomization. This study focused particularly on situations where CRTs are accompanied by a common complication, namely, treatment noncompliance or, more generally, intervention nonadherence. In CRTs, compliance may be…

Popular methods for fitting unidimensional item response theory (IRT) models to data assume that the latent variable is normally distributed in the population of respondents, but this can be unreasonable for some variables. Ramsay-curve IRT (RC-IRT) was developed to detect and correct for this nonnormality. The primary aims of this article are to…

A number of important applications require the clustering of binary data sets. Traditional nonhierarchical cluster analysis techniques, such as the popular K-means algorithm, can often be successfully applied to these data sets. However, the presence of masking variables in a data set can impede the ability of the K-means algorithm to recover the…

Infant-control habituation methodology, although serving the research community well, has never been carefully analyzed. A main use is to equate infants in their level of habituation prior to experimental manipulations in a posthabituation phase. When studied analytically and with simulation, it is found to have serious difficulties. It…

Variants of adaptive Bayesian procedures for estimating the 5% point on a psychometric function were studied by simulation. Bias and standard error were the criteria to evaluate performance. The results indicated a superiority of (a) uniform priors, (b) model likelihood functions that are odd symmetric about threshold and that have parameter…