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Assessing Secular Trends in Blood Pressure: A Multiple-Imputation Approach

 

作者: DanielF. Heitjan,   J.Richard Landis,  

 

期刊: Journal of the American Statistical Association  (Taylor Available online 1994)
卷期: Volume 89, issue 427  

页码: 750-759

 

ISSN:0162-1459

 

年代: 1994

 

DOI:10.1080/01621459.1994.10476808

 

出版商: Taylor & Francis Group

 

关键词: Bayesian bootstrap;Hot deck;Incomplete data;Missing data;Observational study;Predictive-mean matching

 

数据来源: Taylor

 

摘要:

The National Center for Health Statistics makes available data from three national health evaluation surveys that it has conducted since 1960: NHES I (1960-1962), NHANES I (1971-1975), and NHANES II (1976-1980). There has been considerable interest in using these data to assess secular trends in cardiovascular risk factors such as blood pressure (BP). Unfortunately, underlying trends in BP are confounded with trends in physician treatment of hypertension over the same period; in the early 1960s it was rare to treat hypertension, whereas by the late 1970s it had become quite common. Our approach to estimating the underlying trends is to take untreated BP to be the variable of interest and to consider it missing in those subjects who are under treatment. We then use a multiple-imputation scheme to construct estimates of trend parameters that adjust for the incompleteness of the original data. Because our imputations depend on certain model features that the data cannot address, we form estimates under different models and compare the results. Our analyses suggest that trend estimates are sensitive to the assumed model, and naive estimates that do not adjust for treatment trends appear to be overly optimistic.

 

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