It is known that interventions are hard to assign randomly to subjects in social psychological studies, because randomized control is difficult to implement strictly and precisely. Thus, in nonexperimental studies and observational studies, controlling the impact of covariates on the dependent variables and addressing the robustness of the inferences from the results is very important. This study first focused on examining the sensitivity of a multivalued treatment effect; second, a small simulation study of Impact Threshold of a Confounding Variable (ITCV) was conducted to examine to what degree the ITCV index is affected by test statistics and sample size; and third, whether the different propensity score weighting methods were sensitive enough to examine different levels of the treatment, and how robust the inference can be made on each value treatment, were demonstrated using Teaching and Learning International Survey (TALIS) data. The findings of this study validate the inference that teacher participation can affect their job satisfaction. The results also use an index for the threshold for this inference statement, and for examining the robustness of the sample. The indexed threshold necessary for the impact and necessary to invalidate the inference, and the threshold for sample replacement provide power arguments for internal validity and external validity, respectively, and they also show a clear warrant for sensitivity analysis. Because this is an international survey, the large sample size also makes this argument stronger. Tables and figures are appended.