Clifford C. Clogg

Bio: Clifford C. Clogg is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Population & Latent variable model. The author has an hindex of 35, co-authored 74 publications receiving 7220 citations.

Statistical Methods for Comparing Regression Coefficients Between Models

Abstract: Statistical methods are developed for comparing regression coefficients between models in the setting where one of the models is nested in the other. Comparisons of this kind are of interest whenever two explanations of a given phenomenon are specified as linear models. In this case, researchers should ask whether the coefficients associated with a given set of predictors change in a significant way when other predictors or covariates are added as controls. Simple calculations based on quantities provided by routines for regression analysis can be used to obtain the standard errors and other statistics that are required. Results are also given for the class of generalized linear models (e.g., logistic regression, log-linear models, etc.). We recommend fundamental change in strategies for model comparison in social research as well as modifications in the presentation of results from regression or regression-type models.

Handbook of statistical modeling for the social and behavioral sciences

Abstract: Casual Inference in the Social and Behavioral Sciences. Missing Data. Specification and Estimation of Mean Structures. The Analysis of Contingency Tables. Latent Class Models. Panel Analysis for Metric Data. Panel Analysis for Qualitative Variables. Analysis of Event Histories. Random Coefficient Models. Index.

The Structure of Intergenerational Exchanges in American Families

Abstract: Intergenerational support is analyzed using data from the National Survey of Families and Households. The authors find evidence that a systematic latent structure of intergenerational exchange characterizes the giving and receiving of support. Overall, one-half of Americans do not routinely engage in giving or receiving relationships with their parents and only about one in 10 are engaged in extensive exchange relationships. Parents are assisted more often in situations of poor health, and more often receive assistance when they have young children. Assistance in time of need is not uniform and is rarely extensive. Intergenerational assistance is constrained by family structure and the needs and resources of each generation. African-Americans are consistently less likely than whites to be involved in intergenerational assistance. In each generation, men receive as much altruistic support as women; higher levels of giving and receiving of aid among American women are due to their greater involvement in exc...

Inference from Iterative Simulation Using Multiple Sequences

Abstract: The Gibbs sampler, the algorithm of Metropolis and similar iterative simulation methods are potentially very helpful for summarizing multivariate distributions. Used naively, however, iterative simulation can give misleading answers. Our methods are simple and generally applicable to the output of any iterative simulation; they are designed for researchers primarily interested in the science underlying the data and models they are analyzing, rather than for researchers interested in the probability theory underlying the iterative simulations themselves. Our recommended strategy is to use several independent sequences, with starting points sampled from an overdispersed distribution. At each step of the iterative simulation, we obtain, for each univariate estimand of interest, a distributional estimate and an estimate of how much sharper the distributional estimate might become if the simulations were continued indefinitely. Because our focus is on applied inference for Bayesian posterior distributions in real problems, which often tend toward normality after transformations and marginalization, we derive our results as normal-theory approximations to exact Bayesian inference, conditional on the observed simulations. The methods are illustrated on a random-effects mixture model applied to experimental measurements of reaction times of normal and schizophrenic patients.

Missing data: Our view of the state of the art.

Abstract: Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, discourage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art.

A comparison of methods to test mediation and other intervening variable effects.

Abstract: A Monte Carlo study compared 14 methods to test the statistical significance of the intervening variable effect. An intervening variable (mediator) transmits the effect of an independent variable to a dependent variable. The commonly used R. M. Baron and D. A. Kenny (1986) approach has low statistical power. Two methods based on the distribution of the product and 2 difference-in-coefficients methods have the most accurate Type I error rates and greatest statistical power except in 1 important case in which Type I error rates are too high. The best balance of Type I error and statistical power across all cases is the test of the joint significance of the two effects comprising the intervening variable effect.

Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods.

Abstract: The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the bias-corrected bootstrap the best method overall.

Sexual dysfunction in the United States: prevalence and predictors.

Abstract: ContextWhile recent pharmacological advances have generated increased public interest and demand for clinical services regarding erectile dysfunction, epidemiologic data on sexual dysfunction are relatively scant for both women and men.ObjectiveTo assess the prevalence and risk of experiencing sexual dysfunction across various social groups and examine the determinants and health consequences of these disorders.DesignAnalysis of data from the National Health and Social Life Survey, a probability sample study of sexual behavior in a demographically representative, 1992 cohort of US adults.ParticipantsA national probability sample of 1749 women and 1410 men aged 18 to 59 years at the time of the survey.Main Outcome MeasuresRisk of experiencing sexual dysfunction as well as negative concomitant outcomes.ResultsSexual dysfunction is more prevalent for women (43%) than men (31%) and is associated with various demographic characteristics, including age and educational attainment. Women of different racial groups demonstrate different patterns of sexual dysfunction. Differences among men are not as marked but generally consistent with women. Experience of sexual dysfunction is more likely among women and men with poor physical and emotional health. Moreover, sexual dysfunction is highly associated with negative experiences in sexual relationships and overall well-being.ConclusionsThe results indicate that sexual dysfunction is an important public health concern, and emotional problems likely contribute to the experience of these problems.