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Repeated-Imputation Inference

rii[if] [in],impvar(varname)[robust]:estimate command

Description

riiis a prefix command that runs multiple imputations of a model based on the value of the multiple imputation variable.riihas been tested on: probit, tobit, cnreg, and regress.riiuses the repeated-imputation inference (RII) technique to derive OLS regression coefficients, estimates of the standard error of the coefficients, test statistics for individual coefficients and a model test statistic. RII is based on Bayesian theory, and is applicable to linear and nonlinear models, and to models estimated by both least squares and maximum likelihood. The RII technique incorporates the variability in the data due to missing data into the estimate of the standard error of the mean.Note: The command submitted to

riicannot contain aniforinsinceriisubsets the data to each value of the imputation variable.ifand/orincan be use inriilike so:

. rii if mvar <= 5 in 1/50000 , imp(mvar): regress y x1 x2 x3 x4 year89year90

. rii if mvar <= 5 , imp(mvar): regress y x1 x2 x3 x4 year89 year90

. rii in 1/50000 , imp(mvar): regress y x1 x2 x3 x4 year89 year90

Paper rii is based onMontalto, Catherine Phillips & Sung, Jaimie. (1996). Multiple imputation in the 1992 Survey of Consumer Finances. Financial Counseling and Planning, Vol. 7, pp. 133-46.

Options

impvar(varname)is a required option that specifies a numeric variable that identifies the multiple imputations with which to run the submitted command.

Saved results

riisaves the following ine():Scalars

e(N_imps)number of imputationse(N)number of observationsMacros

e(depvar)name of dependent variablee(prefix)riie(command)command run by riie(cmdline)command as typede(cmdname)name of command run by riie(cmd)name of command run by riie(properties)b VMatrices

e(b)coefficient vectore(V)variance-covariance matrix of the estimatorse(obs_per_imp)number of observations per imputationFunctions

e(sample)marks estimation sample

Examples

. rii , imp(mvar): probit x1 x2 x3, robust

. rii if mvar < 6, imp(mvar): tobit amtspt x1 x2 x3 x4, ll(0) ul(25000)

. rii , imp(mvar): cnreg y x1 x2 x3 x4 year89 year90, censored(cen)

. rii , imp(mvar): reg y x1 x2 [pweight=pop]Instead of using dprobit use probit and then run mfx:

. rii , impvar(mvar): probit y x1 x2 x3

. mfx

AuthorsDavid T. Robinson Center for Entrepreneurship and Innovation Duke University's Fuqua School of Business davidr@duke.edu Dan Blanchette The Carolina Population Center University of North Carolina - Chapel Hill, USA dan_blanchette@unc.edu

Also seeOn-line: probit, tobit, cnreg, and regress