Study Details
Language on this page comes directly from the program model developer or authors. It does not necessarily reflect the official position of the U.S. Department of Health and Human Services or any federal agency.
Smith, Kim, et al. Interim Impacts of the Gender Matters Program. Mathematica Policy Research, Princeton, NJ: 2015b.
Smith, Kimberly V., Claire Dye, Dana Rotz, Elizabeth Cook, Kristina Rosinsky, and Mindy Scott. "Final Impacts of the Gender Matters Program." Princeton, NJ: Mathematica Policy Research, September 2016.
Gender Matters (GEN.M)
Program Information
Evaluation Setting
Study Sample
Research Design
754
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18
NA = Not available. This means the authors did not report the information in the manuscripts associated with the studies we reviewed.
a This information was not available whenever authors did not report information for the treatment and comparison groups separately on outcome means, standard deviations, and/or sample sizes.
b Authors reported that the program effect (impact) estimate is statistically significant with a p-value of less than 0.05 based on a two-tailed test.
c For some outcomes, having less of that outcome is favorable. In those cases, an effect with a negative sign is favorable to the treatment group (that is, the treatment group had a more favorable outcome than the comparison group, on average).
d An effect shows credibly estimated, statistically significant evidence whenever it has a p-value of less than 0.05 based on a two-tailed test, includes the appropriate adjustment for clustering (if applicable), and it is not based on an endogenous subgroup.