Randomization should be employed whenever possible but the use of carefully controlled nonrandomized data to estimate causal effects is a reasonable and necessary procedure in many cases. (Author/BJG)

When the precise basis of selection effect on correlation and regression equations is unknown but can be modeled by selection on a variable that is highly but not perfectly related to observed scores, the selection effects can lead to the commonly observed "overprediction" results in studies of predictive bias. (Author/PN)

The unbiased estimate of a "treatment effect" reached by analysis of covariance in a nonrandomized experiment would often require that a different covariate be used in each treatment. A sufficient but unlikely condition for an unbiased estimate is that the covariate for each treatment is (1) the complete covariate that predicts the outcome as…

Accurate estimation of variance components used in generalizability theory is essential for the theory to be viewed as an efficacious mechanism for studying the reliability and validity of a measurement procedure. This paper explores two alternatives for dealing with the apparent instability of small sample size used in determining the accuracy of…