The outcome variables in this study were assumed to follow different distributions and therefore a variety of regressions were estimated. To demonstrate statistical significance of estimated results consistently and as simply as possible, we chose to show p-values for all estimates, be it odds ratios or marginal effects. P-values range from 0 to 1 and are the observed "tail" probability of a statistic being at least as extreme as the particular observed value when the null hypothesis is true. Usually the null hypothesis in our study is that the estimated coefficient is 0. For example, if the estimated coefficient of male relative to female from the OLS regression of percent time employed yields 0.02 and the t-statistic is 3.45 with the associated p-value at 0.01, then the probability is as high as 99 percent (1 minus p-value) that the true effect of sex on percent time employed is not 0. The lower the p-value, the higher the statistical significance of the estimated result. The cutoff for statistical significance in this report is a p-value of 0.1.