| pool.lori {lori} | R Documentation |
The pool.lori method aggregates lori multiple imputation results. Multiple imputation allows to produce estimates of missing values, as well as intervals of variability. The classical procedure is to perform multiple imputation using the mi.lori method, and to aggregate them using the pool.lori method.
Description
The pool.lori method aggregates lori multiple imputation results. Multiple imputation allows to produce estimates of missing values, as well as intervals of variability. The classical procedure is to perform multiple imputation using the mi.lori method, and to aggregate them using the pool.lori method.
Usage
pool.lori(res.mi)
Arguments
res.mi |
a multiple imputation result from the function mi.lori |
Value
pool.impute |
a list containing the pooled means (mean) and variance (var) of the imputed values |
pool.alpha |
a list containing the pooled means (mean) and variance (var) of the row effects |
pool.beta |
a list containing the pooled means (mean) and variance (var) of the column effects |
pool.epsilon |
a list containing the pooled means (mean) and variance (var) of the covariate effects |
pool.theta |
a list containing the pooled means (mean) and variance (var) of the interactions |
Examples
X <- matrix(rnorm(50), 25)
Y <- matrix(rpois(25, 1:25), 5)
res <- mi.lori(Y, X, 10, 10, 2)
poolres <- pool.lori(res)