List and endorsement experiments are
becoming increasingly popular among social scientists as indirect
survey techniques for sensitive questions. When studying issues
such as racial prejudice and support for militant groups, these
survey methodologies may improve the validity of measurements by
reducing non-response and social desirability biases. We develop a
statistical test and multivariate regression models for comparing
and combining the results from list and endorsement experiments. We
demonstrate that when carefully designed and analyzed, the two
survey experiments can produce substantively similar empirical
findings. Such agreement is shown to be possible even when these
experiments are applied to one of the most challenging research
environments: contemporary Afghanistan. We find that both
experiments uncover similar patterns of support for the
International Security Assistance Force among Pashtun respondents.
Our findings suggest that multiple measurement strategies can
enhance the credibility of empirical conclusions.
Open-source software is
available for implementing the proposed methods (Last Revised, April
2013)