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A simulated 1:4 matched case-control dataset for illustrating ncc_indi and cv.ncc_indi. The object contains both an internal cohort and an external cohort in case-control form, so that the external cohort can be used as individual-level external information when fitting the conditional logistic regression model with external integration.

This is the individual-level analog of ExampleData_cc_lowdim: rather than supplying beta_external only, the external cohort is provided in full (subject-level matched-set data).

Usage

data(ExampleData_cc_indi)

Format

A list containing two cohorts:

internal

A list with components for the internal matched case-control study:

z

Numeric matrix of covariates of dimension \(1000\times 6\) with columns named Z1Z6.

y

Integer vector of binary outcomes (1=case, 0=control).

stratum

Integer vector identifying the matched set for each observation (200 unique strata, exactly one case and four controls per set).

external

A list with the same component names as internal, containing 500 matched sets (\(n = 2500\)) with the same 1:4 matching design, intended to be passed as the external cohort to ncc_indi.

Details

Both the internal and external cohorts are 1:4 matched case-control studies on six covariates Z1Z6. The matching design (one case and four controls per stratum) is preserved in both cohorts, which is required by ncc_indi and the stratum-level fold construction in cv.ncc_indi.

Examples

data(ExampleData_cc_indi)
str(ExampleData_cc_indi, max.level = 2)
#> List of 2
#>  $ internal:List of 3
#>   ..$ z      : num [1:1000, 1:6] 1.4209 1.8271 1.2201 -0.0173 1.0239 ...
#>   .. ..- attr(*, "dimnames")=List of 2
#>   ..$ y      : int [1:1000] 0 1 0 0 0 0 0 1 0 0 ...
#>   ..$ stratum: int [1:1000] 1 1 1 1 1 2 2 2 2 2 ...
#>  $ external:List of 3
#>   ..$ z      : num [1:2500, 1:6] -1.523 0.711 -0.674 -0.956 -0.805 ...
#>   .. ..- attr(*, "dimnames")=List of 2
#>   ..$ y      : int [1:2500] 0 0 0 1 0 0 0 0 0 1 ...
#>   ..$ stratum: int [1:2500] 1 1 1 1 1 2 2 2 2 2 ...