An imputation method for non-ignorable missing data in studies of blood pressure

Statistics in Medicine
N R Cook

Abstract

In studies with repeated measures of blood pressure (BP), particularly in trials of hypertension prevention, BP measurements often become censored once a participant commences antihypertensive medication. When prescribed by non-study physicians under uncontrolled conditions, the missing data mechanism is non-ignorable and may bias the BP effects of interest. I propose a method that models the distribution of BPs measured by non-study physicians and their relation to study BPs using random effects models. If treated for hypertension, I assume that BP measured outside the study is greater than a clinical cutpoint, such as diastolic BP > or = 90 mmHg. I then compute estimates for the missing study BPs conditional on previously observed study BPs and treatment for hypertension. Multiple imputation is used to model the variability of the BP values and adjust the standard error estimates of the parameters. Examples are given using simulated data and data from the weight loss intervention of phase I of the Trials of Hypertension Prevention.

Associated Clinical Trials

Citations

Mar 12, 2011·Statistics in Medicine·Nicholas MascaMartin D Tobin
Jun 26, 2010·Clinical Trials : Journal of the Society for Clinical Trials·Shona FieldingCraig Ramsay
Oct 25, 2006·Clinical Trials : Journal of the Society for Clinical Trials·N R Cook
Sep 17, 2004·Journal of Human Hypertension·S K KumanyikaUNKNOWN Trials of Hypertension Prevention Collaborative Research Group
Feb 25, 2005·Health Economics·Jan B Oostenbrink, Maiwenn J Al
Feb 12, 2008·Pharmacoepidemiology and Drug Safety·Joseph A C DelaneySamy Suissa

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