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Using a Counting Process Method to Impute Censored Follow-Up Time Data

Author

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  • Jimmy T. Efird

    (Centre for Clinical Epidemiology and Biostatistics (CCEB), School of Medicine and Public Health, The University of Newcastle (UoN), Callaghan, NSW 2308, Australia)

  • Charulata Jindal

    (Centre for Clinical Epidemiology and Biostatistics (CCEB), School of Medicine and Public Health, The University of Newcastle (UoN), Callaghan, NSW 2308, Australia)

Abstract

Censoring occurs when complete follow-up time information is unavailable for patients enrolled in a clinical study. The process is considered to be informative (non-ignorable) if the likelihood function for the model cannot be partitioned into a set of response parameters that are independent of the censoring parameters. In such cases, estimated survival time probabilities may be biased, prompting the need for special statistical methods to remedy the situation. The problem is especially salient when censoring occurs early in a study. In this paper, we describe a method to impute censored follow-up times using a counting process method.

Suggested Citation

  • Jimmy T. Efird & Charulata Jindal, 2018. "Using a Counting Process Method to Impute Censored Follow-Up Time Data," IJERPH, MDPI, vol. 15(4), pages 1-10, April.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:4:p:690-:d:139755
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    References listed on IDEAS

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    3. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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