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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

Emotion regulation has been associated with perceived health in rheumatoid arthritis, which is diagnosed three times more often in women than men. Our aim was to examine gender differences in styles of emotion regulation (ambiguity, control, orientation, and expression) and gender-specificity of the associations between emotion regulation and perceived health (psychological well-being, social functioning, physical functioning, and disease activity) in 244 female and 91 male patients with rheumatoid arthritis. Women reported more emotional orientation than men, but did not differ from men with regard to ambiguity, control, and expression. Structural equation modelling showed that relationships between emotion regulation and perceived health were more frequent and stronger for women than men. This held especially for the affective dimension of health, while associations were similar for both women and men with regard to social and physical functioning. Only for women, the association between ambiguity and disease activity was significant, which appeared to be mediated by affective functioning. The observations that women are more emotionally oriented than men and that emotion regulation is more interwoven with psychological health in women than men, support the usefulness of a gender-sensitive approach in research and health care of patients with rheumatoid arthritis.

/pdf/gender-differences-in-emotion-regulation-and-relationships-j2frxlqr2p.pdf

Gender Differences in Emotion Regulation and Relationships with Perceived Health in Patients with Rheumatoid Arthritis

Within the latent growth curve model, time-invariant covariates are generally modeled on the subject level, thereby estimating the effect of the covariate on the latent growth parameters. Incorporating the time-invariant covariate in this manner may have some advantages regarding the interpretation of the effect but may also be incorrect in certain instances. In this article we discuss a more general approach for modeling time-invariant covariates in latent growth curve models in which the covariate is directly regressed on the observed indicators. The approach can be used on its own to get estimates of the growth curves corrected for the influence of a 3rd variable, or it can be used to test the appropriateness of the standard way of modeling the time-invariant covariates. It thus provides a test of the assumption of full mediation, which states that the relation between the covariate and the observed indicators is fully mediated by the latent growth parameters.

/pdf/including-time-invariant-covariates-in-the-latent-growth-1dncsjg6yx.pdf

Including Time-Invariant Covariates in the Latent Growth Curve Model

The analysis of measurement invariance of latent constructs is important in research across groups, or across time. By establishing whether factor loadings, intercepts and residual variances are equivalent in a factor model that measures a latent concept, we can assure that comparisons that are made on the latent variable are valid across groups or time. Establishing measurement invariance involves running a set of increasingly constrained structural equation models, and testing whether differences between these models are significant. This paper provides a step-by-step guide to analysing measurement invariance.

Developmetrics A checklist for testing measurement invariance

http://www.aepc.es/ijchp/articulos_pdf/ijchp-327.pdf

A prospective study of the relation between posttraumatic stress and physical health symptoms

The Randomized Response Technique (RRT) is a survey method especially developed to improve the accuracy of answers to questions on threatening topics. This paper reports the results of two meta-analyses on RRT studies, the first on the results of six individual validation studies, and the second on 31 comparative studies. The focus of these metaanalyses was on the performance of RRTs compared to conventional question-answer methods. A multilevel analysis with three levels (studies, conditions, and sensitive items) was used to compare the effects of data collection methods across different studies. As effect size for the individual validation studies we used the percentage of incorrect answers and as effect size for the comparative studies we used the standardized difference. Results indicated an overall positive effect for RRT across studies compared to the other methods. This positive effect is stronger as the topic under investigation becomes more socially sensitive by nature. This makes it opportune to use RRT when sensitive topics are studied. However, both metaanalyses showed a large variance component between studies. We interpret this as an indication that RRT is not under complete control of the researchers using it, and advise careful pretesting of the chosen RRT procedure. meta-analysis of randomized response research 3

Joop J. Hox

Papers

Gender Differences in Emotion Regulation and Relationships with Perceived Health in Patients with Rheumatoid Arthritis

Including Time-Invariant Covariates in the Latent Growth Curve Model

Developmetrics A checklist for testing measurement invariance

A prospective study of the relation between posttraumatic stress and physical health symptoms

Meta-Analysis of Randomized Response Research: 35 Years of Validation.