ex_coxquad: Simulated example data with time to event outcome and...
In smcfcs: Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification
ex_coxquad R Documentation
Simulated example data with time to event outcome and quadratic covariate effects
Description
A dataset containing simulated data where a time to event outcome depends quadratically
on a partially observed covariate.
Usage
ex_coxquad
Format
A data frame with 1000 rows and 6 variables:
- t
Time to event or censoring
- d
Binary indicator of whether event occurred or individual was censored
- z
Fully observed covariate, with linear effect on outcome (on log hazard scale)
- x
Partially observed normally distributed covariate, with quadratic effect on outcome (on log hazard scale)
- xsq
The square of x, which thus has missing values also
- v
An auxiliary variable (i.e. not contained in the substantive model)
smcfcs documentation built on June 22, 2024, 10 a.m.
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| ex_coxquad | R Documentation |
Simulated example data with time to event outcome and quadratic covariate effects
Description
A dataset containing simulated data where a time to event outcome depends quadratically on a partially observed covariate.
Usage
ex_coxquad
Format
A data frame with 1000 rows and 6 variables:
- t
Time to event or censoring
- d
Binary indicator of whether event occurred or individual was censored
- z
Fully observed covariate, with linear effect on outcome (on log hazard scale)
- x
Partially observed normally distributed covariate, with quadratic effect on outcome (on log hazard scale)
- xsq
The square of x, which thus has missing values also
- v
An auxiliary variable (i.e. not contained in the substantive model)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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