Document Type

Article

Publication Date

4-16-2020

Publication Title

bioRxiv

First page number:

1

Last page number:

14

Abstract

Given the time- and resource-intense nature of human subjects research, we have developed a more intelligent approach to participant recruitment above and beyond random sampling that leverages pilot or preliminary results to reduce the overall number of participants needed for recruitment from an existing electronic cohort or database. Using open-access data from the General Social Survey (GSS) of the National Opinion Research Center, we generated pilot and validation datasets through a simulation to establish moderate and weak relationships based on linear regression. We then compared the performance of our residual-matching method against random sampling in their probabilities of achieving a given level of statistical power as well as their prediction accuracies. Results showed that the residual-matching method was superior to random sampling, yielding smaller sample sizes with equivalent mean square error. We therefore advocate the use of residual matching when scaling up pilot studies to conserve time and resources in larger follow-up studies.

Keywords

Citizen science; Recruitment; Simulation; Resource efficiency

Disciplines

Design of Experiments and Sample Surveys | Physical Sciences and Mathematics | Statistics and Probability

File Format

PDF

File Size

700 KB

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Creative Commons License

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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