Cultural Trait Transmission and Missing Data as Sources of Bias in Cross-Cultural Survey Research

Abstract

Ember, Ember, and Low (2007) recently reported male mortality in warfare and environmental pathogen stress as statistically significant predictors of nonsororal polygyny. Two sources of bias can be identified in their data analysis: 1) omitted variable bias due to not including a variable for cultural trait transmission, that is, Galton's Problem; and 2) bias caused by extensive deletion of cases when the basic assumption required by listwise deletion, that the missing data are missing completely at random, does not hold. We first re-estimated Ember et al.'s model after adding a trait transmission variable using the listwise deletion subsample, and then again after using contemporary multiple imputation procedures to deal with missing data. Our findings indicate that the significant effects reported for male mortality and pathogen stress are the result of these two sources of bias. The only significant predictor of the world-wide distribution of nonsororal polygyny in the current analyses is cultural trait transmission.