Logistic regression was used to examine predictors of post-disaster PTSD pooled across surveys. Predictors were entered in blocks, beginning with socio-demographics, followed by disaster characteristics, prior TE and CA exposure, and prior mental disorders. All models included dummy control variables for surveys. Logistic regression coefficients and standard errors were exponentiated and are reported as odds ratios (ORs) with 95% confidence intervals (CIs). Statistical significance of individual ORs was evaluated using 0.05-level two-sided tests based on the design-based Taylor-series method (Wolter, 1985) implemented in the SAS software system (SAS Institute Inc., 2008). Design-based F tests were used to evaluate significance of predictor sets, with numerator degrees of freedom equal to number of predictors and denominator degrees of freedom equal to number of geographically clustered sampling error calculation units containing randomly selected disasters across surveys (n = 138), minus the sum of primary sample units from which these sampling error calculation units were selected (n = 100) and one less than the number of variables in the predictor set (Reed, 2007), resulting in 38 denominator degrees of freedom in evaluating univariate predictions and fewer in evaluating multivariate predictions.
