A Multiple-Imputation Analysis of a Case-Control Study of the Risk of Primary Cardiac Arrest Among Pharmacologically Treated Hypertensives

Archived Abstract of Former PSC Researcher

Raghunathan, Trivellore, and David S. Siscovick. 1996. "A Multiple-Imputation Analysis of a Case-Control Study of the Risk of Primary Cardiac Arrest Among Pharmacologically Treated Hypertensives." Applied Statistics, 45(3): 335-352.

A multiple-imputation method is developed for analysing data from an observational study where some covariate values are not observed. A hybrid approach is presented where the imputations are created under a Bayesian model involving an extended set of variables, although the ultimate analysis may be based on a regression model with a smaller set of variables. The imputations are the random draws from the posterior predictive distribution of the missing values, given the observed values. Gibbs sampling under an extension of the Olkin-Tate general location-scale model is used for the imputation. The method proposed is used to analyse data from a population-based case-control study investigating the association between drug therapy and primary cardiac arrest among pharmacologically treated hypertensives. The sensitivity of the inference to the assumptions about the mechanism for the missing data is explored by creating imputations under several non-ignorable mechanisms for missing data. The sampling properties of the estimates from the hybrid multiple-imputation approach are compared with those based on the complete data and maximum likelihood approaches through simulated data sets. This comparison suggest that much efficiency can be gained through the hybrid approach. Also, the multiple-imputation approach seems to be fairly robust to departures from the assumed normality unless the actual distribution of the continuous covariates is very skew.

http://links.jstor.org/sici?sici=0035-9254%281996%2945%3A3%3C335%3AAMAOAC%3E2.0.CO%3B2-0

Keywords:
Gibbs Sampling Logistic Regression Non-Ignorable Mechanism Odds Ratios Olkin-Tate Model Sensitivity Analysis

Browse | Search | Next

PSC In The News

RSS Feed icon

Shaefer comments on the Cares Act impact in negating hardship during COVID-19 pandemic

Heller comments on lasting safety benefit of youth employment programs

More News

Highlights

Dean Yang's Combatting COVID-19 in Mozambique study releases Round 1 summary report

Help Establish Standard Data Collection Protocols for COVID-19 Research

More Highlights


Connect with PSC follow PSC on Twitter Like PSC on Facebook