ex_linquad: Simulated example data with continuous outcome and quadratic...
In jwb133/bootmi: Bootstrap Inference for Multiple Imputation
ex_linquad R Documentation
Simulated example data with continuous outcome and quadratic covariate effects
Description
A dataset containing simulated data where the outcome depends quadratically
on a partially observed covariate.
Usage
ex_linquad
Format
A data frame with 1000 rows and 5 variables:
- y
Continuous outcome
- z
Fully observed covariate, with linear effect on outcome
- x
Partially observed normally distributed covariate, with quadratic effect on outcome
- xsq
The square of x, which thus has missing values also
- v
An auxiliary variable (i.e. not contained in the substantive model)
jwb133/bootmi documentation built on Sept. 22, 2024, 10:14 p.m.
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| ex_linquad | R Documentation |
Simulated example data with continuous outcome and quadratic covariate effects
Description
A dataset containing simulated data where the outcome depends quadratically on a partially observed covariate.
Usage
ex_linquad
Format
A data frame with 1000 rows and 5 variables:
- y
Continuous outcome
- z
Fully observed covariate, with linear effect on outcome
- x
Partially observed normally distributed covariate, with quadratic effect on outcome
- 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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