Evaluate an expression in multiple imputed datasets

Performs a computation of each of imputed datasets in data.

Usage

# S3 method for class 'mids'
with(data, expr, ...)

Arguments

data: An object of type mids, which stands for 'multiply imputed data set', typically created by a call to function mice().
expr: An expression to evaluate for each imputed data set. Formula's containing a dot (notation for "all other variables") do not work.
...: Not used

Value

An object of S3 class mira

Note

Version 3.11.10 changed to tidy evaluation on a quosure. This change should not affect any code that worked on previous versions. It turned out that the latter statement was not true (#292). Version 3.12.2 reverts to the old with() function.

References

van Buuren S and Groothuis-Oudshoorn K (2011). mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(3), 1-67. doi:10.18637/jss.v045.i03

Author

Karin Oudshoorn, Stef van Buuren 2009, 2012, 2020

Examples

imp <- mice(nhanes2, m = 2, print = FALSE, seed = 14221)

# descriptive statistics
getfit(with(imp, table(hyp, age)))
#> Component 1 :
#>      age
#> hyp   20-39 40-59 60-99
#>   no     12     4     3
#>   yes     0     3     3
#> 
#> Component 2 :
#>      age
#> hyp   20-39 40-59 60-99
#>   no     11     4     4
#>   yes     1     3     2
#> 

# model fitting and testing
fit1 <- with(imp, lm(bmi ~ age + hyp + chl))
fit2 <- with(imp, glm(hyp ~ age + chl, family = binomial))
fit3 <- with(imp, anova(lm(bmi ~ age + chl)))