Description ----------- hodgesl implements Hodges-Lehmann aligned rank test of the null hypothesis of no difference in an outcome variable between treated and control observations over matched or stratified sets. The test is an extension of the Wilcoxon signed rank test to matching with multiple controls. It may be employed in testing treatment effect that stratifies the sample on single or multiple covariates, where the number of strata compared to the number of total sample observations is large, and within a stratum each treated subject has more than one matched control. The test is needed when the analyst evaluates average treatment effect and performs a significance test of such effect after optimal matching.
dataname specifies the name of data file for the sample being tested after matching or stratification. varname is the name of outcome variable on which the analyst wants to test the difference between treated and control observations. blockname specifies the variable name that identifies matched or stratified sets. treatname specifies the name of the dichotomous variable identifying treatment conditions (i.e., treatname = 1 if the observation receives treatment, and treatname = 0 if the observation is a control). savfile specifies the name of a saved data file for future analysis. Output and Return Values ------------------------ After running hodgesl, Stata returns the sample average treatment effect in the metric of the outcome variable tx_effect, Hodges-Lehmann mean statistic HL_mean, Hodges-Lehmann standard-error statistic HL_se, the test statistic z that is the ratio of HL_mean and HL_se, and is subject to a standard normal distribution, and the p-value of z via which the analyst can perform a significance test of a nondirectional hypothesis (i.e., perform a two-tailed test) or a directional hypothesis (i.e. perform a one-tailed test).
After running hodgesl, savfile contains mean of the outcome and number of observations for each treatment condition by matched set. The data file can be used for postestimation analysis.
The analyst can use return list immediately after running hodgesl to see statistics saved for further analysis.
Examples -------- . hodgesl cds lwss97 fm kuse fm_results
. hodgesl "C:\PSA\chapter5\cds.dta" lwss97 fm kuse "C:\tmp\fm_results" . return list . use "C:\tmp\fm_results", clear . list
References ---------- Guo, S., & Fraser, M. (2009). Propensity score analysis: Statistical methods and applications. Thousand Oaks, CA: Sage Publications, Inc. Lehmann, E. L. (2006). Nonparametrics: Statistical methods based on ranks (Rev. ed., pp.132-141) New York: Springer.
Rosenbaum, P.R. (2002) Observational Studies. 2nd edition. New York: Springer. Author ------ Shenyang Guo University of North Carolina at Chapel Hill sguo@email.unc.edu
Also see: ---------