Logistic regression is one of the most fundamental tools in predictive analytics. Graduate business analytics students are often familiarized with implementation of logistic regression using Python, R, SPSS, or other software packages. However, an understanding of the underlying maximum likelihood model and the mechanics of estimation are often…

The deleterious effects of maternal depression on child emotional and behavioral development are well documented, yet many children exposed to maternal depression experience positive outcomes. The aim of this study was to identify psychosocial factors associated with the emotional-behavioral resilience of four-year-old children of first-time…

General chemistry is a gateway course that impacts the STEM trajectory of tens of thousands of students each year, and its role in the introductory curriculum as well as its pedagogical design are the center of an ongoing debate. To investigate the role of general chemistry in the curriculum, we report the results of a posthoc analysis of 10 years…

Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

In this paper, we explore the use and efficacy of fiscal incentive policies in California school districts. We ask whether districts with high need for teachers with English as a second language (ESL) or special education credentials are more likely to implement incentives targeting these teachers. We find mixed evidence that districts align their…

Concern and research involving the overrepresentation of African American students in the category of mild intellectual disability (MID) has existed for over four decades. Yet, little research focuses exclusively on the disproportionate representation of African American students at the secondary level. This study analyzed the National…

Although student persistence in graduate programs is widely regarded as an important topic in the literature of higher education, many such works focus on the completion of studies. This paper examines the dynamics of attrition resulting in either delayed or non-completion of doctoral studies. Administrative data of 294 Ph.D. students at Makerere…

Doubly bounded continuous data are common in the social and behavioral sciences. Examples include judged probabilities, confidence ratings, derived proportions such as percent time on task, and bounded scale scores. Dependent variables of this kind are often difficult to analyze using normal theory models because their distributions may be quite…

Secondary respondent data are underutilized because researchers avoid using these data in the presence of substantial missing data. The authors reviewed, evaluated, and tested solutions to this problem. Five strategies of dealing with missing partner data were reviewed: (a) complete case analysis, (b) inverse probability weighting, (c) correction…

In education randomized control trials (RCTs), the misreporting of student outcome data could lead to biased estimates of average treatment effects (ATEs) and their standard errors. This article discusses a statistical model that adjusts for misreported binary outcomes for two-level, school-based RCTs, where it is assumed that misreporting could…

Using data from the National Longitudinal Transition Study-2, this article examines the relationships among three of Wehmeyer's components of self-determination (autonomy, empowerment, and self-realization) and subsequent reported access to postsecondary education in transitioning youths receiving Supplemental Security Income benefits. Results of…

In randomized control trials (RCTs) of educational interventions, there is a growing literature on impact estimation methods to adjust for missing student outcome data using such methods as multiple imputation, the construction of nonresponse weights, casewise deletion, and maximum likelihood methods (see, for example, Allison, 2002; Graham, 2009;…

This study investigates parameters affecting the likelihood of passing school facility construction bonds by local district election. Using statewide data from Michigan, this study analyzes school bond data for urban (n = 30), suburban (n = 164), small town (n = 70), and rural (n = 241) school districts that held capital improvement bond elections…

Nonlinear common factor models with polynomial regression functions, including interaction terms, are fitted by simultaneously estimating the factor loadings and common factor scores, using maximum likelihood and least squares methods. A Monte Carlo study gives support to a conjecture about the form of the distribution of the likelihood ratio…

The application of multidimensional item response theory (IRT) models to longitudinal educational surveys where students are repeatedly measured is discussed and exemplified. A marginal maximum likelihood (MML) method to estimate the parameters of a multidimensional generalized partial credit model for repeated measures is presented. It is shown…