The article focuses on estimating effects in nonrandomized studies with two outcome measurement occasions and one predictor variable. Given such a design, the analysis approach can be to include the measurement at the previous time point as a predictor in the regression model (ANCOVA), or to predict the change-score of the outcome variable…

This study reviews the international literature of empirical educational research to examine the application of logistic regression. The aim is to examine common practices of the report and interpretation of logistic regression results, and to discuss the implications for educational research. A review of 130 studies suggests that: (a) the…

Randomized controlled trials are not always feasible in educational research, so researchers must use alternative methods to study treatment effects. Propensity score matching is one such method for observational studies that has shown considerable growth in popularity since it was first introduced in the early 1980s. This paper outlines the…

In studies of educational achievement, students' self-reported number of books in the family home is a frequently used proxy for social, cultural, and economic background. Absent hard evidence about what this variable captures or how well, its use has been motivated by strong associations with student outcomes. I show that these associations rest…

The purpose of this article is to describe effect coding as an alternative quantitative practice for analyzing and interpreting categorical, race-based independent variables in higher education research. Unlike indicator (dummy) codes that imply that one group will be a reference group, effect codes use average responses as a means for…

In response to questions in which a "wh"-term interacts with a universal quantifier in object position, such as "Who picked every toy?," children as old as 5 years of age often provide a list, pairing toys with the people who picked each of them. This response pattern is unexpected, it has been claimed, because children appear…

Selection bias is a persistent, and often hidden, problem in educational research. It is the primary obstacle standing in between increasingly available large education datasets and the ability to make valid causal inferences to inform policymaking, research, and practice (Stuart, 2010). This article provides an accessible discussion on the…

In the 21st century, attainment of a college degree is more important than ever to achieve economic self-sufficiency, employment, and an adequate standard of living. Projections suggest that by 2020, 65% of jobs available in the U.S. will require postsecondary education. This reality creates an unprecedented demand for higher education, and…

Although women's representation in higher education nears parity with men at the undergraduate level, this representation diminishes as one ascends the academic ranks. Because gender gaps in the "elite" activity of international research collaborations might contribute to the underrepresentation of women in the upper ranks, we ask if…

Despite being criticized as unrepresentative and misleading, retention and graduation rates are an important part of college-search web sites and accountability systems, and they frequently have been used as indicators of institutional quality and effectiveness in educational research. Retention and graduation rates are often compared over time…

Online education is rapidly becoming a significant method of course delivery in higher education. Consequently, instructors analyze student performance in an attempt to better scaffold student learning. Learning analytics can provide insight into online students' course behaviors. Archival data from 167 graduate level education students enrolled…

Purpose: Across the United States, a large percentage of school districts are in need of facility improvements to provide safe and adequate buildings to facilitate student learning. To finance new construction, school districts traditionally have put proposals before local voters to fund construction through issuing long-term bonds to finance…

Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…

The purpose of this project is to demonstrate the practical methods developed to utilize a dataset consisting of both multivariate and multilevel effect size data. The context for this project is a large-scale meta-analytic review of the predictors of academic achievement. This project is guided by three primary research questions: (1) How do we…

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…