Negative attitudes towards lesbian women and gay men continue to exist in Southeast Asian countries. This study identified predictors of homonegativity that are generally consistent across the countries in the region. Using data from the seventh round of World Values Survey, we obtained parsimonious country-level logistic regression models for six of the 11 Southeast Asian countries: Indonesia (n = 3,200), Malaysia (n = 1,313), Myanmar (n = 1,200), the Philippines (n = 1,200), Thailand (n = 1,500), and Vietnam (n = 1,200). Results suggest that four values and one demographic variable are consistent predictors of homonegativity in Southeast Asia. Endorsements of equality, choice, and agnosticism were found to be consistent predictors of lower levels of homonegative attitudes, while the opposite was observed for endorsement of relativism and older people. That there are some consistent cultural predictors of lower levels of homonegativity may suggest a common emancipative logic in Southeast Asia. On the whole, however, the findings suggest that there may be no uniform (Southeast) Asian values system that constitutes sexual prejudice. This foregrounds the need for more contextually-sensitive and culturally-informed models of homonegativity to understand why negative attitudes persist in some countries but not in others, and to also guide the crafting of interventions that are more relevant to each country.
Data analysis techniques that rely on standard statistical tools and algorithms often encounter problems when dealing with data sets that have large sample sizes. In this study, two statistical tests done in conducting simple linear regression analysis were revisited. In particular, the study simulated the effects of large sample sizes and amount of contamination in the data due to non-sampling errors on the false positive rate of the Kolmogorov-Smirnov (K-S) test in testing for normality of error terms. The study also characterized the effects of varying sample size and amount of contamination in the data on the false negative rate of the t-test in testing the significance of a regression coefficient. Lastly, an optimality index was developed to determine the sample sizes and the values of the percent noise at which both the false positive rate of the K-S test and the false negative rate of the t-test are minimized.
