Semi-parametric Frailty Models

Semi-Parametric Frailty Models is a class of survival regression models that incorporate unobserved random effects (frailties) to account for heterogeneity or clustering in time-to-event data, where the baseline hazard function is left unspecified, allowing nonparametric estimation while the frailty distribution and regression parameters are parametrically modeled.

63

Publications

2.8K

Citations

149

Authors

104

Institutions

Publications per year

2017–2026

13

Authors

149

  1. MG
    Malka Gorfine

    Tel Aviv University, Israel

    7 publications · 203 citations

    7

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  2. LH
    Li Hsu

    Fred Hutch Cancer Center, United States

    7 publications · 203 citations

    7

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  3. DM
    David M. Zucker

    Hebrew University of Jerusalem, Israel

    4 publications · 88 citations

    4

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  4. YL
    Youngjo Lee

    Seoul National University, South Korea

    4 publications · 90 citations

    4

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  5. ID
    Il Do Ha

    Seoul National University, South Korea

    4 publications · 68 citations

    4

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1–5 of 149

Venues

  1. Biometrics

    11 publications · 542 citations

    11

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  2. PubMed

    Repository · 4 publications · 86 citations

    4

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  3. Statistics in Medicine

    4 publications · 183 citations

    4

    h-index

  4. 4

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  5. Journal of Statistical Planning and Inference

    3 publications · 64 citations

    3

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1–5