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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

/pdf/the-effect-of-computer-assisted-interviewing-on-data-quality-32zlcu3qof.pdf

The Effect of Computer-assisted Interviewing on Data Quality. A Review:

/pdf/from-theoretical-concept-to-survey-question-49ytdrt2bk.pdf

From Theoretical Concept to Survey Question

This study examined the effects of daily support exchanges in couples facing multiple sclerosis (MS). Two issues were examined: the imbalance between received and provided support, and the extent to which reciprocal exchanges of received and provided support are associated with end-of-day well-being (positive and negative mood and selfesteem). Guided by equity theory, we expected that one-sided support provision or receipt would be harmful for well-being for both patients and partners. We argued that these negative outcomes could be offset by reciprocating support, that is, when both partners receive and provide support. Sixty-one patients and their partners filled out questionnaires on demographics and disease-related characteristics and subsequently completed computerized daily diaries for 14 days. At the end of each day, both partners completed diaries on end-of-day mood, self-esteem, received and provided emotional and instrumental support, and several control variables (daily hassles and MS-related symptoms for patients). Reciprocity in instrumental support transactions was associated with higher levels of self-esteem among both patients and partners. However, the other results all showed independent effects of support received and provided. Patients’ well-being was related to providing emotional support and instrumental support, whereas partners’ well-being was related to receiving emotional support from patients.

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Receiving and providing support in couples dealing with multiple sclerosis: a diary study using an equity perspective

Interviewers play an important role in gaining cooperation in surveys. There is empirical evidence for a considerable variation in response rates between interviewers. Despite this, research on the role of the interviewer in nonresponse is relatively scarce. Past research showed that interviewer experience plays a role in gaining respondent cooperation, and recently the importance of the "doorstep' interaction has been emphasized. In this article, we describe the tactics for fighting nonresponse, as reported by experienced interviewers. We also explore the relationship between favored tactics of interviewers and interviewers' individual response rate.

Interviewers' tactics for fighting survey nonresponse

This study applies ordinal confirmatory factor analysis for multiple groups to assess equivalence of scale, random errors and systematic (nonrandom) errors of attitudinal questions surveyed on rating scales under different survey modes (Face-to-Face [F2F], Telephone, Paper, and Web). Empirical findings from a large-scale experiment are presented. Consistent with theoretical expectations, interviewer- and self-administered surveys measured all assessed questions on systematically different scales, with different systematic bias, and with differing extents of random error. These measurement effects were absent when comparing Paper with Web or F2F with Telephone. It is concluded that modes impact primarily systematic measurement effects affecting multiple items equally. Interviewer- and self-administered modes should only be combined with great care in mixed-mode surveys that focus on attitudinal constructs. Combining Paper and Web or Telephone and F2F are the viable options. Thereby choosing the self-admini...

Joop J. Hox

Papers

The Effect of Computer-assisted Interviewing on Data Quality. A Review:

From Theoretical Concept to Survey Question

Receiving and providing support in couples dealing with multiple sclerosis: a diary study using an equity perspective

Interviewers' tactics for fighting survey nonresponse

Measurement Effects of Survey Mode on the Equivalence of Attitudinal Rating Scale Questions