Clustered survival data with left-truncation

Frank Eriksson; Torben Martinussen; Thomas H. Scheike

doi:10.1111/sjos.12157

Clustered survival data with left-truncation

Frank Eriksson^*, Torben Martinussen, Thomas H. Scheike

^*Corresponding author for this work

Section of Biostatistics

4 Citations (Scopus)

Abstract

Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry. Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties are investigated via simulation studies, and the suggested estimators are used in a study of prostate cancer based on the Finnish twin cohort where a twin pair is included only if both twins were alive in 1974.

Original language	English
Journal	Scandinavian Journal of Statistics
Volume	42
Issue number	4
Pages (from-to)	1149–1166
Number of pages	18
ISSN	0303-6898
DOIs	https://doi.org/10.1111/sjos.12157
Publication status	Published - 1 Dec 2015

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title = "Clustered survival data with left-truncation",

abstract = "Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry. Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties are investigated via simulation studies, and the suggested estimators are used in a study of prostate cancer based on the Finnish twin cohort where a twin pair is included only if both twins were alive in 1974.",

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T1 - Clustered survival data with left-truncation

AU - Eriksson, Frank

AU - Martinussen, Torben

AU - Scheike, Thomas H.

PY - 2015/12/1

Y1 - 2015/12/1

N2 - Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry. Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties are investigated via simulation studies, and the suggested estimators are used in a study of prostate cancer based on the Finnish twin cohort where a twin pair is included only if both twins were alive in 1974.

AB - Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry. Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties are investigated via simulation studies, and the suggested estimators are used in a study of prostate cancer based on the Finnish twin cohort where a twin pair is included only if both twins were alive in 1974.

KW - Clustered data

KW - Counting process

KW - Delayed entry

KW - Frailty

KW - Left-truncation

KW - Survival

KW - Twin register

KW - Two-stage

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JF - Scandinavian Journal of Statistics

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ER -

Clustered survival data with left-truncation

Abstract

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