2003•Statistics in MedicineRequires access

Comparing Cox and parametric models in clinical studies

Alessandra Nardi, MICHAEL SCHEMPER

Open publisher page 129 citations

Abstract

Parametric models are only occasionally used in the analysis of clinical studies of survival although they may offer advantages over Cox's model. In this paper, we report experiences that we have made fitting parametric models to data sets from different clinical trials mainly performed at the Vienna University Medical School. We emphasize the role of residuals for discriminating among candidate models and judging their goodness of fit. The effect of misspecification of the baseline distribution on parameter estimates and testing has been explored. The results from parametric analyses have always been contrasted with those from Cox's model.

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What this paper is about

Parametric models are only occasionally used in the analysis of clinical studies of survival although they may offer advantages over Cox's model. In this paper, we report experiences that we have made fitting parametric models to data sets from different clinical trials mainly performed at the Vienna University Medical School. We emphasize the role of residuals for discriminating among candidate models and judging their goodness of fit. The effect of misspecification of the baseline distribution on parameter estimates and testing has been explored. The results from parametric analyses have always been contrasted with those from Cox's model.

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Available abstract

Parametric models are only occasionally used in the analysis of clinical studies of survival although they may offer advantages over Cox's model. In this paper, we report experiences that we have made fitting parametric models to data sets from different clinical trials mainly performed at the Vienna University Medical School. We emphasize the role of residuals for discriminating among candidate models and judging their goodness of fit. The effect of misspecification of the baseline distribution on parameter estimates and testing has been explored. The results from parametric analyses have always been contrasted with those from Cox's model.

Key concepts: Parametric statistics, Parametric model, Goodness of fit, Proportional hazards model, Econometrics, Survival analysis, Semiparametric model, Statistics

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