Abstract

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.

Software

list: Statistical Methods for the Item Count Technique and List Experiment — CRAN / GitHub

endorse: R Package for Analyzing Endorsement Experiments — CRAN / GitHub

Related Papers

Kenny, Christopher, Cory McCartan, Tyler Simko, and Kosuke Imai (2024). ``Census officials must constructively engage with independent evaluations.'' Proceedings of the National Academy of Sciences (Letter), Vol. 121, No. 11, e2321196121.

Kenny, Christopher, Cory McCartan, Shiro Kuriwaki, Tyler Simko, and Kosuke Imai (2024). ``Evaluating Bias and Noise Induced by the U.S. Census Bureau's Privacy Protection Methods.'' Science Advances, Vol 10, No. 18 (May), pp. 1-13.

McCartan, Cory, Tyler Simko, and Kosuke Imai (2024). ``Rejoinder: We Can Improve the Usability of the Census Noisy Measurements File.'' Harvard Data Science Review, Vol. 6, No. 2 (Spring).

McCartan, Cory, Tyler Simko, and Kosuke Imai (2023). ``Making Differential Privacy Work for Census Data Users.'' Harvard Data Science Review, Vol. 5, No. 4 (Fall).

McCartan, Cory, Tyler Simko, and Kosuke Imai (2023). ``Researchers need better access to US Census data.'' Science, Vol. 380, No. 6648 pp. 902-903.

Kenny, Christopher T., Shiro Kuriwaki, Cory McCartan, Evan T.R. Rosenman, Tyler Simko, and Kosuke Imai (2021). ``The Use of Differential Privacy for Census Data and its Impact on Redistricting: The Case of the 2020 U.S. Census.'' Science Advances, Vol. 7, No. 7 (October), pp. 1-17.

Chou, Winston, Kosuke Imai, and Bryn Rosenfeld (2020). ``Sensitive Survey Questions with Auxiliary Information.'' Sociological Methods & Research, Vol. 49, No. 2 (May), pp. 418-454.

Blair, Graeme, Winston Chou, and Kosuke Imai (2019). ``List Experiments with Measurement Error.'' Political Analysis, Vol. 27, No. 4 (October), pp. 455-480.

Hirose, Kentaro, Kosuke Imai, and Jason Lyall (2017). ``Can Civilian Attitudes Predict Insurgent Violence?: Ideology and Insurgent Tactical Choice in Civil War.'' Journal of Peace Research, Vol. 51, No. 1 (January), pp. 47-63. Winner of the Nils Petter Gleditsch Article of the Year Award. Story by Princeton's communication office.

Rosenfeld, Bryn, Kosuke Imai, and Jacob Shapiro (2016). ``An Empirical Validation Study of Popular Survey Methodologies for Sensitive Questions.'' American Journal of Political Science, Vol. 60, No. 3 (July), pp. 783-802.

Blair, Graeme, Kosuke Imai, and Yang-Yang Zhou (2015). ``Design and Analysis of the Randomized Response Technique.'' Journal of the American Statistical Association, Vol. 110, No. 511 (September), pp. 1304-1319.

Lyall, Jason, Yuki Shiraito, and Kosuke Imai (2015). ``Coethnic Bias and Wartime Informing.'' Journal of Politics, Vol. 77, No. 3 (July), p. 833-848.

Imai, Kosuke, Bethany Park, and Kenneth Greene (2015). ``Using the Predicted Responses from List Experiments as Explanatory Variables in Regression Models.'' Political Analysis, Vol. 23, No. 2 (Spring), pp. 180-196. Translated in Portuguese and Reprinted in Revista Debates Vol. 9, No 1.

Lyall, Jason, Graeme Blair, and Kosuke Imai (2013). ``Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan.'' American Political Science Review, Vol. 107, No. 4 (November), pp. 679-705. Winner of the Pi Sigma Alpha Award.

Blair, Graeme and Kosuke Imai (2012). ``Statistical Analysis of List Experiments.'' Political Analysis, Vol. 20, No. 1 (Winter), pp. 47-77.

Bullock, Will, Kosuke Imai, and Jacob Shapiro (2011). ``Statistical Analysis of Endorsement Experiments: Measuring Support for Militant Groups in Pakistan.'' Political Analysis, Vol. 19, No. 4 (Autumn), pp. 363-384.

Imai, Kosuke (2011). ``Multivariate Regression Analysis for the Item Count Technique.'' Journal of the American Statistical Association, Vol. 106, No. 494 (June), pp. 407-416. (featured article)