Declares a nested case-control (NCC) sample drawn from a cohort by risk-set (incidence-density) sampling: at each event time, the case is matched to ratio controls sampled from those still at risk. The classical analysis treats each sampled risk set as a stratum in a conditional partial likelihood (survival::clogit/coxph); because the controls are sampled from the risk set, the conditional odds ratio equals the hazard ratio with no rare-disease assumption.
Usage
nested_cc(strata, time, ratio = NULL)
Arguments
strata
A non-empty character vector naming the column(s) that identify the sampled risk sets (the matched-set id).
time
A single character string naming the event/entry time column that defines the risk sets. Carried for the inclusion-probability weight and weighted-Cox estimators built on this design.
ratio
NULL or a single whole number >= 1. Controls sampled per case.
Value
A matchatr_design object of type“nested_cc” carrying the strata, time, and ratio, with a weight_spec flagged for inclusion-probability weighting.
References
Thomas DC (1977). Addendum to "Methods of cohort analysis: appraisal by application to asbestos mining" (Liddell FDK, McDonald JC, Thomas DC). Journal of the Royal Statistical Society, Series A 140(4):469-491.
Prentice RL, Breslow NE (1978). Retrospective studies and failure time models. Biometrika 65(1):153-158.
Goldstein L, Langholz B (1992). Asymptotic theory for nested case-control sampling in the Cox regression model. The Annals of Statistics 20(4):1903-1928.
Samuelsen SO (1997). A pseudolikelihood approach to analysis of nested case-control studies. Biometrika 84(2):379-394.
See Also
case_cohort(), counter_matched(), matcha()
Other design constructors: case_cohort(), counter_matched(), matched_cc(), two_phase(), unmatched_cc()
Examples
library("matchatr")nested_cc(strata ="set", time ="t")
<matchatr_design>
Type: Nested case-control
Strata: set
Time: t
Weights: inclusion-probability
nested_cc(strata ="set", time ="t", ratio =3)
<matchatr_design>
Type: Nested case-control
Strata: set
Time: t
Ratio: 3:1
Weights: inclusion-probability