It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…

When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…

This Monte Carlo study investigates the beneficiary effect of including auxiliary variables during estimation of confirmatory factor analysis models with multiple imputation. Specifically, it examines the influence of sample size, missing rates, missingness mechanism combinations, missingness types (linear or convex), and the absence or presence…