Sociological Methods & Research

Panel studies are statistical studies in which two or more variables are observed for two or more subjects at two or more points in time. Cross-lagged panel studies are those studies in which the variables are continuous and divide naturally into two sets. Focus is on estimating and testing the effects, or impacts, of each set of variables on the other. In the regression approach the cross-lagged model is formulated as a multivariate regression model and regression methods are used to make inferences about the parameters. We contribute to this approach by decomposing the dependence in such models into lagged dependence and cotemporal dependence and developing three strategies for assessing the degree of dependence. We present hypothesis tests for these strategies and then demonstrate the three by analyzing a set of psychiatric panel data.

This article presents an expository discussion of the use of odds, odds ratios, and functions of odds ratios as an aid to the interpretation of log-linear parameters. While there have been some previous presentations on the use of odds ratios, this method has never been fully and systematically developed for complex situations, nor have the potential problems of interpretation using odds ratios been discussed. The presentation in this article more fully elaborates the possible modes of drawing contrasts with odds ratios using any of the three common parameterizations of a log-linear model (ANOVA-like, regression-like, and logit). The sampling distribution and the calculation of standard errors for odds ratios are also discussed as are some cautions on the interpretation of odds ratios. A data analysis of unemployment using polytomous variables illustrates the application and interpretation of the odds-ratio approach.

A simultaneous latent class analysis of survey data from 1978 and 1983 is used to clarify the current controversy over whether opposition to abortion reflects a conservative sexual morality or pro-life values. Results indicate that the “pro-life” and “pro-choice” dichotomy represents an incomplete characterization of the American public—a third group, characterized by a conservative sexual morality and opposition to discretionary abortion, but not to nondiscretionary abortion, must also be included in the classification. The evidence indicates that from 1978 to 1983 this sexually conservative group decreased from one-third to one-fourth of the U.S. adult population and that the “pro-choice” increased to approximately one-half of the population over the same period. The proportion of the population characterized as the “pro-life” class remained stable at approximately 1 of 4 over the same time period.

The use of logistic regression to estimate a discrete-time hazard model is discussed. The derivation of linkage between the results of the estimation of the logistic regression equations and the summary measures of the life table is presented. We argue that the method is responsive to the needs of a variety of researchers, requires few assumptions, and is straightforward to implement. An example is presented where the determinants of the timing of entry into motherhood in eight Asian countries is analyzed.

In a recent edition of this journal, Borgatta et al. (1986), using hypothetical data, illustrated how the results produced by principal components analysis can be substantially different from those of common factor analysis. The present article, using seven well-known data sets, extends their work into the empirical domain, and also compares the results of the maximum likelihood factor analysis model with those of the principal components model. The results strongly support those of Borgatta et al. Indeed, the discrepancies in the empirical results reported here are often larger than their hypothetical example suggests. It was found that, when comparing the performance of the principal components model with the common factor and maximum likelihood models, differences can be expected to occur in (1) the magnitudes of the factor loadings, (2) the signs attached to the factor loadings, and, most important, (3) the interpretation of the factors themselves.

Guided by the model of the question-answer process as developed by Cannell and his coworkers, our main research question focused on how interviewers should behave in order to obtain adequate responses in survey interviews. A field experiment was conducted in which the interviewers adopted one of two behavioral styles, namely, a personal versus a formal style of interviewing. The dependent variables concerned measures of accuracy, social desirability, and the degree of relevant as well as irrelevant information. In addition, by experimentally manipulating the interviewer's alleged opinion, it was possible to ascertain conformity effects. Two different hypotheses were proposed to account for the effect of interviewing style on the dependent variables. The motivation hypothesis proposed that a personal style, compared with a formal style, would motivate the respondent to do well on the task and to give responses that would be as accurate and as adequate as possible. According to the ingratiation hypothesis, respondents interviewed in a personal style would be more inclined to attempt to ingratiate themselves with the interviewer, leading to more socially desirable responses, conformity, and irrelevant information. The results supported the motivation hypothesis. We contend that both motivation and ingratiation are important mechanisms in the question-answer process. However, it may be easier to influence the respondent's motivational level by means of the style of interviewing or other interviewing techniques than the respondent's ingratiation tendencies.