extract_MIdata() function)
and runs an analysis function on each of them.R/miAnalyze.R
miAnalyze.RdTakes multiply imputed datasets (as generated by the extract_MIdata() function)
and runs an analysis function on each of them.
miAnalyze(formula, family = NULL, data, pool = TRUE)a two sided model formula (see formula).
only for glm: a description of the distribution and link
function to be used in the model. This can be a character string
naming a family function, a family function or the result of a
call to a family function. (For more details see below and
family.)
the output object of extract_MIdata() function.
logical. If TRUE, estimates from each imputed data set will be pooled together according to Rubin's rules. Default is TRUE.
A list containing
list of estimated coefficients and standard error from each imputed data.
pooled estimates based Rubin's rule if pool = TRUE.
rubin_rules applies Rubin's rules (Rubin, 1987) for pooling together
the results from a multiple imputation procedure. The pooled point Estimate is
is the average across the point estimates from the complete-data analyses.
The SE is the square-root of the sum of two terms representing the within-variance
and the between-variance (see Little-Rubin (2002)). The function also returns
95% confidence interval, based on the estimated pooled degrees of freedom
that can be used for inference based on the t-distribution.