Transcription of teffects psmatch — Propensity-score matching - Stata
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teffects psmatch — Propensity-score matching - Stata
psmatch Propensity-score matchingDescriptionQuick startMenuSyntaxOptionsRemarks and examplesStored resultsMethods and formulasReferencesAlso seeDescriptionteffects psmatchestimates the average treatment effect (ATE) and average treatment effect onthe treated (ATET) from observational data by Propensity-score matching (PSM).PSMestimators imputethe missing potential outcome for each subject by using an average of the outcomes of similar subjectsthat receive the other treatment level. Similarity between subjects is based on estimated treatmentprobabilities, known as propensity scores. The treatment effect is computed by taking the average ofthe difference between the observed and potential outcomes for each psmatchaccepts a continuous, binary, count, fractional, or nonnegative [TE] teffects introor [TE] teffects intro advancedfor more information about estimatingtreatment effects from observational startATEoftreatonyestimated byPSMusing a logistic model fortreatonxand indicators for levelsof categoric
Propensity-score matching uses an average of the outcomes of similar subjects who get the other treatment level to impute the missing potential outcome for each subject. The ATE is computed by taking the average of the difference between the observed and potential outcomes for each subject.
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