dstat: Stata module to compute summary statistics and distribution functions including standard errors and optional covariate balancing

Jann, Ben (2020). dstat: Stata module to compute summary statistics and distribution functions including standard errors and optional covariate balancing. [Software & Other Digital Items]

Archive (Version 1.0.2) dstat20201127.zip - Published Version Available under License BORIS Standard License. Download (59kB)

dstat unites a variety of methods to describe (univariate) statistical distributions. Covered are density estimation, histograms, cumulative distribution functions, probability distributions, quantile functions, lorenz curves, percentile shares, and a large collection of summary statistics such as classical and robust measures of location, scale, skewness, and kurtosis, as well as inequality and poverty measures. Particular features of the command are that it provides consistent standard errors supporting complex sample designs for all covered statistics and that the simultaneous analysis of multiple variables across multiple subpopulations is possible. Furthermore, the command supports covariate balancing based on reweighting techniques (inverse probability weighting and entropy balancing), including appropriate correction of standard errors. Standard error estimation is implemented in terms of influence functions, which can be stored for further analysis, for example, using RIF regression.

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