Ermagun, AlirezaLevinson, David M2016-04-282016-04-282015https://hdl.handle.net/11299/179812The current research provides a test framework to understand whether and to what extent increasing public transit use and accessibility by transit affect health. To this end, the effect of transit mode share and accessibility by transit on general health, body mass index, and height are investigated, while controlling for socioeconomic, demographic, and physical activity factors. The coefficient-p-value-sample-size chart is created and effect size analysis are conducted to explore whether the transit use is practically significant. Building on the results of the analysis, we found that the transit mode share and accessibility by transit are not practically significant, and the power of large-sample misrepresents the effect of transit on public health. The results, also, highlight the importance of data and variable selection by portraying a significant correlation between transit use and height in a multivariate regression analysis. What becomes clear from this study is that in spite of the mushrooming interdisciplinary studies in the nexus of transportation and health arena, researchers often propose short- and long-term policies blindly, while failing to report the inherent explanatory power of variables. We show that there is a thin line between false positive and true negative results. From the weakness of p-values perspective, further, we strove to alert both researchers and practitioners to the dangerous pitfall deriving from the power of large- samples. Building the results on just significance and sign of the parameter of interest is worthless, unless the magnitude of effect size is carefully quantified post analysis.enPublic transit; BRFSS data; ACS data; Accessibility to jobs; p-hackingWorking Paper