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Using Multivariate Statistics

The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic pooling. This article documents mice, which extends the functionality of mice 1.0 in several ways. In mice, the analysis of imputed data is made completely general, whereas the range of models under which pooling works is substantially extended. mice adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs. Imputation of categorical data is improved in order to bypass problems caused by perfect prediction. Special attention is paid to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. mice can be downloaded from the Comprehensive R Archive Network. This article provides a hands-on, stepwise approach to solve applied incomplete data problems.

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mice: Multivariate Imputation by Chained Equations in R

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

Multiple Imputation for Nonresponse in Surveys

Statistical Analysis with Missing Data

Self-Administered Questionnaires

This article examines the nonresponse among ethnic minorities in the Netherlands. We have constructed a structural equation model with various response outcomes, controlling the effect of ethnicity on the response outcomes for various socio-economic and socio-demographic variables. The effect of ethnicity on response is almost entirely mediated by the degree of urbanization. We have also performed multiple group analyses to examine differences between ethnic groups in the response outcome predictors. Here again, we note that urbanization has a negative effect on the response probabilities in all the ethnic groups and in particular on the contact probabilities. This negative effect is somewhat larger, however, among sampled units with a non-Western background.

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Nonresponse Among Ethnic Minorities: A Multivariate Analysis

Small Samples in Multilevel Modeling

Background: Patients with rheumatoid arthritis face the challenge of adjusting to adverse health consequences and accompanying emotions. Styles of emotion regulation may affect health.Purpose: The objective is to examine associations between styles of emotion regulation and perceived health, consisting of psychological well-being, social functioning, physical functioning, and disease activity.Methods: Principal component analysis was used to summarize styles of emotion regulation of 335 patients with rheumatoid arthritis. Relationships between emotion regulation and perceived health were examined with structural equation modeling.Results: Four styles of emotion regulation were identified: ambiguity, control, orientation, and expression. Ambiguity and control were mutually correlated, as were orientation and expression. Styles of emotion regulation were not uniquely related to perceived physical functioning and disease activity. Emotional ambiguity and orientation were related to poorer, whereas expression and control were related to more favorable psychological well-being and social functioning.Conclusions: Our cross-sectional study suggests that emotion regulation is not of direct importance for perceived somatic health of patients with rheumatoid arthritis, but it may be of importance for psychological well-being and social functioning, and perhaps through this route for somatic health. The more conscious and controlled aspects of control and expression are positively related to psychosocial health, and the more unconscious automatic aspects of ambiguity and orientation are negatively related. Changing emotion regulation will potentially affect psychosocial health. It would be worthwhile to verify this possibility in prospective research.

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Styles of emotion regulation and their associations with perceived health in patients with rheumatoid arthritis.

In surveys, interviewers serve as the agents of data collection. Their task includes contacting the target persons, gaining their cooperation, and conducting the interviews according to the rules of standardized interviewing. 

Interviewers are not equally successful at doing their job. They differ both in the quality of the data collected and in the response rate they achieve (Biemer & Lyberg, 2003, pp. 110–11, p. 156ff.). It is often difficult to distinguish to what extent these differences arise from differences among interviewers or from differences between the areas (and the target persons, living in these areas) assigned to the interviewers. Research using interpenetrated sample designs, however, has shown that interviewer effects can remain strong even when area effects are controlled (Campanelli & O’Muircheartaigh, 1999).

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Joop J. Hox

Papers

Self-Administered Questionnaires

Nonresponse Among Ethnic Minorities: A Multivariate Analysis

Small Samples in Multilevel Modeling

Styles of emotion regulation and their associations with perceived health in patients with rheumatoid arthritis.

The Influence of Interviewers’ Contact Behavior on the Contact and Cooperation Rate in Face-to-Face Household Surveys