The ability of universities and colleges to predict the success of admitted students continues to be a key concern of higher education officials. Apart from a desire to see students have successful academic careers, there is also the fiscal reality of greater tuition revenues providing needed support for university budgets. Using administrative…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

Latent change score models (LCS) are conceptually powerful tools for analyzing longitudinal data (McArdle & Hamagami, 2001). However, applications of these models typically include constraints on key parameters over time. Although practically useful, strict invariance over time in these parameters is unlikely in real data. This study…

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…

Student peer effects are well documented. We know far less, however, about peer effects among teachers. We hypothesize that a relatively effective teacher may positively affect the performance of their peers, while a relatively ineffective teacher may negatively impact the performance of other teachers with whom they work closely. Utilizing a…

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

Schools and neighborhoods are thought to be two of the most important contextual influences on student academic outcomes. Drawing on a unique data set that permits simultaneous estimation of neighborhood and school contributions to student test score gains, we analyze the distributions of these contributions to consider the relative importance of…

This paper investigates the impact of early noncognitive skills on social outcomes in adolescence. The child's attention span, approach, prevailing mood and distractibility in early childhood may be crucial predictors for school achievements, health risk behavior, delinquency and autonomy as adolescent. We investigate this issue using a…

Teachers require knowledge of the unique skills that each child brings to the classroom in order to effectively target instruction towards students' learning needs. Despite substantial investments in programs aimed at enhancing teacher knowledge of individual students' skills (KISS), we know surprisingly little about how KISS is distributed or how…

Aside from effects on nearby property values, research is sparse on how foreclosures may generate negative externalities. Employing a unique dataset that matches individual student records from Boston Public Schools--including test scores, demographics, home address moves, and school changes--with real estate records indicating whether the student…

Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)