*! version 0.0.1 apr2021

Title

ivcvscore -- Stata package to compute inverse variance-covariance weighted z-scores.

Syntax

Computes inverse variance-covariance weighted z-scores, following Anderson (2008), to compute indexes.

ivcvscore
varlist
, generate(varname)
[treatment(varname)]

Main
generate(varname) store index in new variable varname

treatment(varname) variable indicating a treatment group. If this is specified, the standardization and variance-covariance matrix will be computed using only control group observations.

Description

ivcvscore computes z-scores to aggregate indicators, using weights that account
for the variance-covariance among indicators. The computation follows Anderson (2008)
and is usefull, e.g., to address the issue of multiple hypothesis testing.

Example

. ivcvscore asset1 asset2 asset3 asset4 , generate(asset_score)

This command will standardize all four asset variables to have mean 0 and variance 1 and
compute the variance-covariance matrix. Rows of the inverse of the variance-covariance matrix
are summed up to obtain weights for each variable. The final index is constructed by summing up all 4 variables, using
these weights and standardizing it to have mean 0 and variance 1.

. ivcvscore asset1 asset2 asset3 asset4 , generate(asset_score) treatment(treat)}

This command will standardize all four variables to have mean 0 and variance 1 in the control group (treat==0) and
compute the variance-covariance matrix (in the control group). Rows of the inverse of the variance-covariance matrix
are summed up to obtain weights for each variable. The final index is constructed by summing up all 4 variables, using
these weights and stardardizing it again, to have mean 0 and variance 1 in the control group.

Citation

Heß, Simon, "ivcvscore: Stata package to compute inverse variance-covariance weighted z-scores."

References

Anderson, M. L. (2008). "Multiple inference and gender differences in the effects of early intervention: A reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects." Journal of the American statistical Association, 103/484, 1481-1495.

Author

Simon Heß, Goethe University Frankfurt.

The latest version of ivcvscore can always be obtained from https://github.com/simonheb/ivcvscore or http://HessS.org.

I am happy to receive comments and suggestions regarding bugs or ideas for improvements/extensions via https://github.com/simonheb/ivcvscore/issues.