We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…

Business analytics courses, such as marketing research, data mining, forecasting, and advanced financial modeling, have substantial predictive modeling components. The predictive modeling in these courses requires students to estimate and test many linear regressions. As a result, false positive variable selection ("type I errors") is…

Research has often found that, when high school grades and SAT scores are used to predict first-year college grade-point average (FGPA) via regression analysis, African-American and Latino students, are, on average, predicted to earn higher FGPAs than they actually do. Under various plausible models, this phenomenon can be explained in terms of…

Based on the test theory model for ordinal measurements proposed by Schulman and Haden, the present paper considers correlations between tests, attenuation, regressions involving true and observed scores, and predictions of test reliability. Comparisons are made to interval test theory. (Author/JKS)

The accuracy and variability of 4 cross-validation procedures and 18 formulas were compared concerning their ability to estimate the population multiple correlation and the validity of the sample regression equation in the population. The investigation included two types of regression, multiple and stepwise; three sample sizes, N = 30, 60, 120;…

A Paradigm for testing concept attainment, comprised of twelve tasks, was formulated. These tasks were hypothesized to form a cumulative hierarchy. Tests were constructed in mathematics and social studies using the paradigm. Data for these tests was analyzed by Kaiser's method for fitting a perfect simplex and Schonemann's method for fitting a…