help mivif

Title

mivif -- Variance inflation factors in
multiply imputed datasets

Syntax

Post estimation after mi estimate : regress

mivif
[, imputations(numlist) uncentered
nofisherz]

Variance inflation factors for variables

mivif varlist [if] [in]
[, imputations(numlist) uncentered
nofisherz]

Stata's factor variable notation is allowed, with the
exception of the ibn. operator in a user supplied varlist.

Description

mivif calculates variance inflation factors in multiply imputed
datasets. See Remarks.

mivif requires the data to be flong
style. To change the style of mi data see
mi convert.

Remarks

According to Rubin's combination rules, the MI point estimate is the
mean of the estimates for each imputed dataset. This value of interest
is assumed to be normally distributed. The VIF for a right-hand-side
variable x1 is calculated as 1/(1 - R2), where R2 is the
coefficient of determination in a model that regresses x1 on the
other right-hand-side variables. To improve normality for R-squared,
Harel (2009) suggests to apply Fisher's z-transformation.

mivif runs the regression of x1 on all other x in each
imputed dataset and calculates the mean of the z-transformed R-squares
as R2_MI. The VIF reported for each variable is calculated as
1/(1 - R2_MI).

Options

imputations(numlist) combines VIFs from imputed datasets
numlist. Default is to pool VIFs from imputed datasets used in
the last estimation, or from all imputed datasets, if a varlist
is supplied. The synonym m(numlist) may be used.

uncentered reports uncentered VIFs. If the previous regression
model is fit without the constant, option uncentered is implied.
See vif.

nofisherz requests that Fisher's z-transformation not be used.

Example

. sysuse auto

. mi set flong

. mi register imputed rep78

. mi impute pmm rep78 price mpg weight foreign ,add(5)

. mi estimate : regress price mpg weight foreign i.rep78

. mivif

Saved results

mivif saves the following in r():

Matrices

r(mivif) result matrix

References

Harel, Ofer (2009). The estimation of R2 and adjusted R2 in incomplete
data sets using multiple imputation. Journal of Applied Statistics,
36(10), 1109-1118.

Author

Daniel Klein, University of Kassel, klein.daniel.81.@gmail.com

Also see

Online: mi, vif

if installed: mibeta, collin