Common source bias has been the focus of much attention. To minimize the problem, researchers have sometimes been advised to take measurements of predictors from one observer and measurements of outcomes from another observer or to use separate occasions of measurement. We propose that these efforts to eliminate biases due to common source…

Incomplete or missing data is a common problem in almost all areas of empirical research. It is well known that simple and ad hoc methods such as complete case analysis or mean imputation can lead to biased and/or inefficient estimates. The method of maximum likelihood works well; however, when the missing data mechanism is not one of missing…

The advantages and disadvantages of balanced incomplete block designs are clarified and their use is demonstrated with an empirical example. A procedure for reducing data of this type to analyzable form is proposed, and an analytical approach that is appropriate for the resulting data is illustrated. (Author/BW)