sens.est: Multivariate Imputation by Chained Equations (Iteration Step...

In davidaarmstrong/SensMiceDA: Multivariate Imputation by Chained Equations (Iteration Step for Sensitivity Analysis)

Description

This is a convenience wrapper function to sens.mice that makes specifying the sensitivity analysis slightly easier and provide output that can be used easily with other convenience functions included here.

Usage

sens.est(mids.obj, vars_vals, digits=2)

Arguments

mids.obj	An object of class mids, typically produces by a previous call to mice() or mice.mids()
vars_vals	A named list identifying the variables to be imputed under the non-ignorable (NI) mechanism and the values that represent the differences between responders and non-responders (see sens.mice for more details). The names must be as they appear in mids.obj[["data"]], but not all variables have to be included, only the one(s) being imputed under the hypothetical NI mechanism.
digits	Number of digits to round the values when they get used to name the elements of the resulting data list.

Value

Returns a list of objects of class mids (multiply imputed data set) with usual components

Author(s)

Noemie Resseguier, with contributions of Roch Giorgi, David Hajage, Yann De Rycke, Xavier Paoletti and Dave Armstrong

References

Resseguier, N., Giorgi, R. and Paoletti, X. (submitted) How to perform a senstivity analysis exploring the impact of missing not at random data under different sceanrios of non response mechanism with the R software.

Rubin, D.B. Multiple Imputation for Nonresponse in Surveys. New York: John Wiley & Sons, 1987.

van Buuren, S., Groothuis-Oudshoorn, K. MICE: Multivariate Imputation by Chained Equations in R.

See Also

mice, mids, sens.mice

davidaarmstrong/SensMiceDA documentation built on July 2, 2019, 12:38 p.m.