Simple matrix sampling planned missing (SMS PD) design, introduce missing data patterns that lead to covariances between variables that are not jointly observed, and create difficulties for analyses other than mean and variance estimations. Based on prior research, we adopted a new multigroup confirmatory factor analysis (CFA) approach to handle…

When data for multiple outcomes are collected in a multilevel design, researchers can select a univariate or multivariate analysis to examine group-mean differences. When correlated outcomes are incomplete, a multivariate multilevel model (MVMM) may provide greater power than univariate multilevel models (MLMs). For a two-group multilevel design…

Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…

The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative…

A multilevel logistic model for estimating a nonlinear trajectory in a multiple-baseline design is introduced. The model is applied to data from a real multiple-baseline design study to demonstrate interpretation of relevant parameters. A simple change-in-levels (?"Levels") model and a model involving a quadratic function…

Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…

In this study, the authors connect 3 streams of literature to develop an instrument for measuring the degree to which principals engage in data-informed decision making on high-impact strategies that are empirically associated with higher student achievement. The 3 literature streams are (a) the importance of data-informed decision making, (b) the…

Data-driven decision-making (DDDM) reform has proven to be an effective means for improving student learning. However, little DDDM reform has happened at the classroom level, and little research has explored variables that influence teacher adoption of DDDM. The authors propose a model in which teachers' sense of efficacy for the skills that…

Using data from the National Study of Postsecondary Faculty and the Early Childhood Longitudinal Study--Kindergarten Class of 1998-99, the author provides guidelines for incorporating weights and design effects in single-level analysis using Windows-based SPSS and AM software. Examples of analyses that do and do not employ weights and design…