A simulation study was conducted to explore the impact of differential item functioning (DIF) on general factor difference estimation for bifactor, ordinal data. Common analysis misspecifications in which the generated bifactor data with DIF were fitted using models with equality constraints on noninvariant item parameters were compared under data…

It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully investigated.…

The piecewise latent growth models (PWLGMs) can be used to study changes in the growth trajectory of an outcome due to an event or condition, such as exposure to an intervention. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM. A comparison of these models is…

Cognitive diagnostic models (CDMs) are a family of psychometric models designed to provide categorical classifications for multiple latent attributes. CDMs provide more granular evidence than other psychometric models and have potential for guiding teaching and learning decisions in the classroom. However, CDMs have primarily been conducted using…

Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques…

The current study compares the progressive-restricted standard error (PR-SE) exposure control method with the Sympson-Hetter, randomesque, and no exposure control (maximum information) procedures using the generalized partial credit model with fixed- and variable-length CATs and two item pools. The PR-SE method administered the entire item pool…

The authors examined the distributional properties of 3 improvement-over-chance, I, effect sizes each derived from linear and quadratic predictive discriminant analysis and from logistic regression analysis for the 2-group univariate classification. These 3 classification methods (3 levels) were studied under varying levels of data conditions,…

Monte Carlo study results show that recently proposed multiple comparison procedures (MCPs) that are not intended to control the familywise error rate had consistently larger true model rates than did familywise error controlling MCPs. (SLD)

Presents an alternative statistical test, BOOT(subscript)med for the two-group situation when a small experimental group is being compared with a large control group. BOOTmed is a between-groups median test derived through bootstrapping techniques. Empirical validation indicates that BOOTmed maintains relatively robust error rates under a variety…

Three types of test were compared: a completion test, a matching test, and a multiple-choice test. The completion test was more reliable than the matching test, and the matching test was more reliable than the multiple-choice test. (Author/BW)

Classification studies are important for practitioners who need to identify individuals for specialized treatment or intervention. When interventions are irreversible or misclassifications are costly, information about the proficiency of different classification procedures becomes invaluable. This study furnishes information about the relative…