Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…

Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…

During the transition period between the use of exclusively old SAT® scores and the use of exclusively new SAT scores, college admission offices will be receiving both types of scores from students. Making an admission decision based on new SAT scores can be challenging at first because institutions have methods, procedures, and models based on…

The objective of this study was to validate a scale for assessment of academic projects. As a complement, we examined its predictive ability by comparing the scores of advised/corrected projects based on the model and the final scores awarded to the work by an examining panel (approximately 10 months after the project design). Results of…

A recent resurgence in logical-rule theories of categorization has motivated the development of a class of models that predict not only choice probabilities but also categorization response times (RTs; Fific, Little, & Nosofsky, 2010). The new models combine mental-architecture and random-walk approaches within an integrated framework and…

This article investigates three types of stage-sequential growth mixture models in the structural equation modeling framework for the analysis of multiple-phase longitudinal data. These models can be important tools for situations in which a single-phase growth mixture model produces distorted results and can allow researchers to better understand…

The National Center for Education Statistics (NCES) continues to be interested in addressing the issue identified by the Government Accountability Office (GAO). With the release of the 2009 National Assessment of Educational Progress (NAEP) reading and mathematics assessments, NCES again had the opportunity to measure the status and change in…

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

The subjective likelihood model [SLiM; McClelland, J. L., & Chappell, M. (1998). Familiarity breeds differentiation: a subjective-likelihood approach to the effects of experience in recognition memory. "Psychological Review," 105(4), 734-760.] and the retrieving effectively from memory model [REM; Shiffrin, R. M., & Steyvers, M. (1997). A model…

Describes and compares eight methods of estimating the parameters of the Zipf distribution. (CLB)

The hypothesis that structured representations can be compared via structural alignment and the prediction that similarity comparisons lead subjects to attend to the matching relational structure of a pair of items were supported through 4 experiments involving 218 undergraduates. Results indicate that similarity involves alignment of structured…

This paper explains how commonality analysis (CA) can be conducted using a specific Statistical Analysis System (SAS) procedure and some simple computations. CA is used in educational and social science research to partition the variance of a dependent variable into its constituent predicted parts. CA determines the proportion of explained…

Two causal models of career development differing in inclusion or noninclusion of variables unique to the experience of the hearing impaired were compared for their ability to explain variance in career maturity, with data from 71 hearing-impaired adolescents. Results suggest neither model is more powerful in explaining career maturity variance.…

Discussion of bibliometrics focuses on methods of predicting the number of new journals carrying relevant articles in the future, using both established parametric approaches and newer empirical methods. Parametric models and empirical Bayes models are used to compare examples using previous bibliographies compiled by Bradford and Kendall. (13…

Mounting pressure in the policy arena to improve teacher productivity either by improving signals that predict teacher performance or through creating incentive contracts based on performance--has spurred two related questions: Are there important determinants of teacher productivity that are not captured by teacher credentials but that can be…