Analysis of a long-term study of neurotic disorder, with insights into the process of non-response

• Published in: Journal of the Royal Statistical Society. Series A, Statistics in society Vol. 169; no. 3; pp. 507 - 523
• Main Authors: Longford, Nicholas T., Tyrer, P., Nur, U. A. M., Seivewright, H.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.07.2006; Blackwell Publishers; Blackwell; Royal Statistical Society
• Series: Journal of the Royal Statistical Society Series A
• Subjects: Analytical estimating; Applications; Datasets; EM algorithm; Estimation bias; Estimation methods; Estimators; Exact sciences and technology; Inference; Inference from stochastic processes; time series analysis; Mathematics; Medical sciences; Missingness not at random; Multiple imputation; Neuroses; Neurotic disorder; Probability and statistics; Sample size; Sciences and techniques of general use; Sensitivity analysis; Standard error; Statistical analysis; Statistical methods; Statistical variance; Statistics; Statistical method; Missing data; Neurotic disorder; Missingness not at random; Sensitivity analysis; Sample size; Prior distribution; Non response; Response process; Long term variation; Multiple imputation; EM algorithm
• ISSN: 0964-1998; 1467-985X
• DOI: 10.1111/j.1467-985X.2006.00406.x

The paper studies the non-response process in a long-term study of neurotic disorder by comparing the analysis based on the responses that were collected by the established practice of interviewing the subjects, at dates arranged in advance (appointments), with the analysis of the nearly complete set of responses that were collected by an extensive effort that involved attempts to interview without seeking a prior agreement. The method of multiple imputation is applied, and its properties are explored in a setting that is not perfectly suited for its application: a relatively small sample size, ordinal score outcomes and the likelihood that the outcomes are missing not at random.