A method requiring minimal computational effort is presented for transforming ordered residuals for purposes of testing the correctness of a regression model. The method maintains the same logical ordering in the transformed residuals as that of the original residuals and is suitable for either correlated or uncorrelated data. (Author/BS)

The concept of change is related to suppressor variable conditions in a least square regression model. The domain of conditions necessary for a weighted change score composite to emerge as an underlying construct is mapped and the information loss through arbitrary assignment of weights to a change composite is explored. (Author/BW)

In the present article it is argued that the Least Squares Simplex Data Matrix Solution does not deal adequately with difficulty factors inasmuch as the theoretical foundation is insufficient. (Author/CB)

The use of segmented polynomial models is explained. Examples of design matrices of dummy variables are given for the least squares analyses of time series and discontinuity quasi-experimental research designs. Linear combinations of dummy variable vectors appear to provide tests of effects in the two quasi-experimental designs. (Author/BW)

It is argued here that the choice of the appropriate method for calculating least squares analysis of variance with unequal sample sizes depends upon the question the experimenter wants to answer about the data. The different questions reflect different null hypotheses. An example is presented using two alternative methods. (Author/BW)

An integrated study of Shine's actualized and pure single-subject behavior functions can produce more information than studying only one function. After summarizing the mathematics behind Shine's viewpoint, an ordinary regression analysis approach to the actualized behavior function is integrated with a time-series analysis approach to the pure…

When sample sizes and/or X intervals are unequal, the analysis of variance computations for trend analysis become quite complicated. This article shows how multiple regression/correlation analysis may be applied in order to accomplish with great simplicity trend analysis under "irregular" conditions. (Author/RL)

A Monte Carlo study explores the robustness assumption in structural equation modeling of using a full information normal theory generalized least-squares estimation procedure on Type I censored data. The efficacy of the following proposed alternate estimation procedures is assessed: asymptotically distribution free estimator and a latent…