Asymptotic Relative Efficiency of Parametric and Nonparametric Survival Estimators

Szilárd Nemes ()
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Szilárd Nemes: BioPharma Early Biometrics and Statistical Innovation, Data Science & AI, BioPharmaceuticals R&D, AstraZeneca, 43183 Gothenburg, Sweden

Stats, 2023, vol. 6, issue 4, 1-13

Abstract: The dominance of non- and semi-parametric methods in survival analysis is not without criticism. Several studies have highlighted the decrease in efficiency compared to parametric methods. We revisit the problem of Asymptotic Relative Efficiency ( A R E ) of the Kaplan–Meier survival estimator compared to parametric survival estimators. We begin by generalizing Miller’s approach and presenting a formula that enables the estimation (numerical or exact) of A R E for various survival distributions and types of censoring. We examine the effect of follow-up time and censoring on A R E . The article concludes with a discussion about the reasons behind the lower and time-dependent A R E of the Kaplan–Meier survival estimator.

Keywords: survival estimates; efficiency; parametric survival; censoring (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2023
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