dataexample.missingdata.unstratified {CaseCohortCoxSurvival} | R Documentation |
Example of case-cohort with unstratified sampling of the subcohort and missing covariate information in phase-two data
Description
List with cohort
.
cohort
is a simulated cohort with 20 000 subjects. It contains:
id
is the subject identifier.
X1
is a continuous baseline covariate. Its measurements are only available for subjects in the case-cohort, i.e., with phase3 = 1
.
X2
is a categorical baseline covariate, with categories 0, 1, and 2. It is measured on all cohort subjects.
X3
is a continuous baseline covariate. Its measurements are only available for subjects in the case-cohort.
status
indicates case status.
event.time
gives the event or censoring time. status
indicates whether the subject experienced the event of interest or was censored.
The sampling of the subcohort was not stratified. 1053 subjects were sampled (independently of case status) from the cohort. subcohort
indicates all these subjects included in the subcohort.
The phase-two sample consisted of the subcohort and any other cases not in the subcohort. phase2
indicates all these subjects included in the phase-two sample.
W3
is a baseline binary variable, based on case status. It is measured on all cohort subjects.
The third phase of sampling was stratified based on the 2 strata defined by W3
. Subjects were sampled from the 2 strata with sampling probabilities 0.9 and 0.8. phase3
indicates all these subjects included in the case-cohort (phase-three sample).
n
gives the number of subjects in the cohort.
m
gives the number of subjects sampled from the cohort (i.e., 1053).
m
and n
would be used to compute the design weights of non-cases. Because all the cases were included in the case-cohort, they would be assigned a design weight of 1.
n.cases
gives the number of cases in the entire cohort.
W3
is a baseline binary variable, based on case status. It is measured on all cohort subjects.
strata.proba.missing
gives the the sampling probablity for the 2 phase-three strata based on W3
and that were used for the third phase of sampling.
weight.true
gives the true design weight (i.e., product of the phase-two and true phase-three design weight).
weight.p2.true
gives true phase-two design weight. They are stratum-specific based on W
.
weight.p3.true
gives the true phase-three design weight. They are stratum-specific based on W3
. weight.p3.true
can be used with argument weights.phase3
of function caseCohortCoxSurvival
, along with argument weights.phase3.type = "design"
.
weight.p3.est
gives the estimated phase-three design weight. They were obtained from W3
, phase2
and phase3
. weight.p3.est
can be used with argument weights.phase3
of function caseCohortCoxSurvival
, along with argument weights.phase3.type = "estimated"
. If in function caseCohortCoxSurvival
weights.phase3 = NULL
but weights.phase3.type = "estimated"
, the phase-three design weights will be estimated from W3
, phase2
and phase3
and should be identical.
weight.est
gives the estimated design weight (i.e., product of the phase-two and estimated phase-three design weight).
References
Etievant, L., Gail, M. H. (2024). Cox model inference for relative hazard and pure risk from stratified weight-calibrated case-cohort data. Lifetime Data Analysis, 30, 572-599.
Etievant, L., Gail, M. H. (2024). Software Application Profile: CaseCohortCoxSurvival: an R package for case-cohort inference for relative hazard and pure risk under the Cox model. Submitted.
Examples
data(dataexample.missingdata.unstratified, package="CaseCohortCoxSurvival")
# Display some of the data
dataexample.missingdata.unstratified$cohort[1:5, ]