Residual plots for linear regression models with censored outcome data: A refined method for visualizing residual uncertainty. Issue 4 (21st April 2017)

• Record Type: Journal Article
• Authors: Law, Martin; Jackson, Dan
• Is Part Of: Communications in statistics. Volume 46:Issue 4(2017)
• Page Start: 3159
• Page End: 3171
• Publication Date: 2017-04-21
• Subjects: Bootstrapping -- Censoring -- Linear models -- Multiple imputation -- Residuals -- Regression diagnostics; 62-09; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2015.1076470
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: Residual plots are a standard tool for assessing model fit. When some outcome data are censored, standard residual plots become less appropriate. Here, we develop a new procedure for producing residual plots for linear regression models where some or all of the outcome data are censored. We implement two approaches for incorporating parameter uncertainty. We illustrate our methodology by examining the model fit for an analysis of bacterial load data from a trial for chronic obstructive pulmonary disease. Simulated datasets show that the method can be used when the outcome data consist of a variety of types of censoring.