Growth curve models are a useful tool for developmentalists because they can estimate an attribute's developmental function by providing a mathematical description of growth on an attribute over time. However, selection of a growth curve model appropriate for estimating individual developmental functions is problematic. The ideal model is the one…

A new approach to time series analysis was developed. It employs a generalized transformation of the observed data to meet the assumptions of the general linear model, thus eliminating the need to identify a specific model. This approach permits alternative computational procedures, based on a generalized least squares algorithm. (Author/BW)

The application and use of hierarchical models is illustrated, using the example of the structure of attitudes toward a new product and a print advertisement. Subjects were college students who responded to seven-point bipolar scales. Hierarchical models were better than nonhierarchical models in conceptualizing attitude but not intention. (GDC)

This study examines the application of the marginal maximum likelihood (MML) EM algorithm to the parameter estimation problem of the three-parameter normal ogive and logistic polychotomous item response models. A three-parameter normal ogive model, the Graded Response model, has been developed on the basis of Samejima's two-parameter graded…

When repeated measures are obtained on the same subjects, interobservation dependencies frequently are generated. The major ways in which these dependencies can arise are illustrated and it is shown how these dependencies may invalidate the use of analysis of variance (ANOVA) and its extension, trend analysis, as methods of evaluating the data of…

Because analyses of reaction-time data are sensitive to aberrant observations and violations of statistical assumptions, a new approach is suggested. In this empirical approach, one applies the same criteria to the problem of selecting a statistical method as one uses to select among alternative experimental procedures. Six criteria are presented…

Title I evaluations using the RMC Model C design depend for their interpretation on the assumption that the regression of posttest on pretest is linear across the cut score level when there is no treatment; but there are many instances where nonlinearities may occur. If one applies the analysis of covariance, or model C analysis, large errors may…