The role of covariates in estimating treatment effects and risk in long-term clinical trials

I. Ford, John David Norrie

    Research output: Contribution to journalArticle

    41 Citations (Scopus)

    Abstract

    This paper reviews previously published work showing that the impact of including covariates in models used to estimate the magnitude of treatment effects in long-term clinical trials is different from what would be predicted from results for the normal linear model. Typically, models with and without covariates cannot simultaneously be valid. A case is made for the use of data from clinical trials to model the future risk and potential benefits of treatment in individual subjects. The methods and results are illustrated using data from the West of Scotland Coronary Prevention Study. Copyright (C) 2002 John Wiley Sons, Ltd.

    Original languageEnglish
    Pages (from-to)2899-2908
    Number of pages9
    JournalStatistics in Medicine
    Volume21
    DOIs
    Publication statusPublished - 2002

    Keywords

    • parameter estimation
    • exponential regression
    • proportional hazards model
    • risk modelling
    • PROPORTIONAL HAZARDS MODEL
    • CORONARY-HEART-DISEASE
    • REGRESSION-MODELS
    • PRIMARY PREVENTION
    • RANDOMIZED TRIALS
    • SURVIVAL ANALYSIS
    • COX MODEL
    • PRAVASTATIN

    Cite this