This paper poses a research question about how a person's work experience affects his or her earnings and shows how the Cumulative Experience Method (CEM) can provide an answer to the question using all available information in a longitudinal data set. (Author/GDC)

A recent recommendation by Holt (EJ 200 576) that coefficients resulting from estimating log-linear and similar models should not be interpreted is argued to be based on lack of clarity about the substantive and theoretical importance of the choice between dummy and effect coding for categorical variables. (Author/GDC)

Defining population diversity as the distribution along a continuum of homogeneity to heterogeneity with respect to one or more variables, measures are described with variance-based interpretations which can be applied to qualitative data. It is possible to use these statistics to define relationships in multivariate distributions. (Author/CTM)

A brief perspective on the analysis and use of aggregate data is presented in this overview. The remainder of this journal (TM 504 431 - 504 435) is devoted to the problems of aggregate data analysis. (JKS)

The relationship between two methods for detecting group effects in nonexperimental data--covariance analysis and contextual analysis--is examined. The examination shows that contextual effects are a special case of the group effect obtained in covariance analysis. (Author/JKS)

Treatments of contextual effects in the social science literature have traditionally focused on statistical phenomena more than on social processes. This article seeks to redress that imbalance by focusing on underlying processes through which social structure and social interaction may impinge upon individuals. (Author/JKS)

Three different uses of ratio variables in aggregate data analysis are discussed: (1) as measures of theoretical concepts, (2) as a means to control an extraneous factor, and (3) as a correction for heteroscedasticity. Alternatives to ratios for each of these cases are discussed and evaluated. (Author/JKS)

Sociological and demographic research often uses variables computed as ratios. When the denominators are highly correlated, and the ratios are used in correlation or regression analysis, a statistical dependency is formed. This article investigates this problem, particularly with respect to partial correlation, multiple regression, and the…

Two methods of analyzing nonorthogonal (uneven cell sizes) cross-classified data sets are compared. The methods are direct standardization and the general linear model. The authors illustrate when direct standardization may be a desirable method of analysis. (JKS)

Three methods of estimating a model of school effects are compared: ordinary least squares; an approach based on the analysis of covariance; and, a residualized input-output approach. Results are presented using a matrix algebra formulation, and advantages of the first two methods are considered. (Author/GK)

The use of a path analysis model to obtain unique, substantively meaningful decomposition of variance among endogenous (independent) variables in the model is argued. This reasoning runs counter to more traditional path analytic work. An example is provided. (Author/JKS)

Social scientists have available a wide array of techniques for the analysis of complex contingency tables. Considerations in choosing from among the techniques are discussed. The theme emphasized here is that the analyst should evaluate the techniques within the context of the substantive questions of the study. (Author/JKS)

Two techniques for interpretation of fitted log-linear models in contingency table analysis are discussed. The use of odds ratios as opposed to direct interpretation of the fitted model is argued for. (Author/JKS)

A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)

An example demonstrates that Joreskog's suggested sufficient conditions for identifying unknown parameters in a confirmatory factor analytic model with correlated factors are not sufficient. Sufficient conditions are presented. (Author/JKS)