RTI uses cookies to offer you the best experience online. By clicking “accept” on this website, you opt in and you agree to the use of cookies. If you would like to know more about how RTI uses cookies and how to manage them please view our Privacy Policy here. You can “opt out” or change your mind by visiting: http://optout.aboutads.info/. Click “accept” to agree.
Summary report of the AAPOR Task Force on Non-probability Sampling
Baker, R., Brick, JM., Bates, NA., Battaglia, M., Couper, MP., Dever, J., Gile, KJ., & Tourangeau, R. (2013). Summary report of the AAPOR Task Force on Non-probability Sampling. Journal of Survey Statistics and Methodology, 1(2), 90-143. https://doi.org/10.1093/jssam/smt008
Survey researchers routinely conduct studies that use different methods of data collection and inference. But for at least the past 60 years, the probability-sampling framework has been used in most surveys. More recently, concerns about coverage and nonresponse coupled with rising costs have led some to wonder whether non-probability sampling methods might be an acceptable alternative, at least under some conditions (Groves 2006; Savage and Burrows 2007).
A wide range of non-probability designs exist and are being used in various settings, including case control studies, clinical trials, evaluation research designs, intercept surveys, and opt-in panels. Generally speaking, these designs have not been explored in detail by survey researchers even though they are frequently used in other applied research fields. Because of their limited use in surveys, the assumptions required to make valid inferences from non-probability samples are not well understood by survey researchers.