Although parallel analysis has been found to be an accurate method for determining the number of factors in many conditions with complete data, its application under missing data is limited. The existing literature recommends that, after using an appropriate multiple imputation method, researchers either apply parallel analysis to every imputed…

Purpose of the Study: Missing data are a common problem encountered while implementing measurement instruments. Yet the extent to which reliability, validity, average discrimination and difficulty of the test results are affected by the missing data has not been studied much. Since it is inevitable that missing data have an impact on the…

Presents general principles for cleaning data sets. Suggests techniques: check for column shifts, data completeness, marginal frequencies, and selected cross-tabulations; examines a sample of cases. Gives strategies for preventing data processing errors. (SK)

The validity of various reliability-corrected procedures for adjusting for initial differences between groups in uncontrolled studies is established for subjects exhibiting linear fan-spread growth. The results are then extended to a nonlinear model of growth. (Author)

Implications of ignoring correlated error on parameter estimates in some simple structural equation models are examined. It is shown analytically and empirically through simulation that ignoring positive between-construct correlated error overestimates the structural parameter linking the two constructs. Effects become more pronounced with…

Given the complexity of classroom reading observations, maintenance of measurement reliability is a concern to researchers. Sources of variation contributing to the unreliability of many measurements may be either (1) lasting and specific, (2) lasting and general, (3) temporary and specific, or (4) temporary and general. Lasting-specific sources…

Generalizability theory, which subsumes classical measurement theory as a special case, provides a general model for estimating the reliability of observational rating data by estimating the variance components of the measurement design. Research data from the "Heart Smart" health intervention program were analyzed as a heuristic tool.…

This paper evaluates the logic underlying various criticisms of statistical significance testing and makes specific recommendations for scientific and editorial practice that might better increase the knowledge base. Reliance on the traditional hypothesis testing model has led to a major bias against nonsignificant results and to misinterpretation…