Calculate confidence intervals datasets created by miset
mici [, indiv] : varlist [in range] [if exp] [, level(#) binomial poisson exposure(varname)]
mici calculates confidence intervals separately for each of the miset datasets and calculates overall confidence intervals by Rubin's rule of combination.
indiv reports the confidence intervals from each of the individual miset datasets, as well as the overall confidence intervals. By default, only the overall confidence interval is displayed.
level specifies the desired level of significance in calculating the confidence intervals. The default is 95%.
binomial specifies that each of the variables in varlist has a binomial distribution, and mici will calculate the binomial standard error for each of the miset datasets and then calculate an overall confidence interval for the corresponding proportion using Rubin's combining rule. If any variable in varlist is not binary (value 0 or 1), an error message is given. Note that the "exact" binomial method is not used since it does not enable application of Rubin's rule.
poisson specifies that the variables are Poisson-distributed counts. Poisson standard errors are calculated from individual miset datasets, and overall confidence intervals are computed using Rubin's rule.
exposure(varname) is used only with poisson. varname contains the total exposure during which the number of events recorded in varlist was observed.
mici can only be used after the multiple datasets have been declared by miset.
. mici: var1 if var2==0, binomial . mici, indiv: var1
Ning Li, Philip Greenwood, and John Carlin, Clinical Epidemiology & Biostatistics Unit, Murdoch Children's Research Institute and University of Melbourne. Email email@example.com
Rubin, D. B. 1987. Multiple Imputation for Nonresponse in Surveys. New York: John Wiley & Sons.
Schafer, J. L. 1997. Analysis of Incomplete Multivariate Data. London: Chapman & Hall.
Online: help for miappend, mimerge, misave, mido, mifit, milincom, mireset, miset