Adaptive Design in Surveys and Clinical Trials: Similarities, Differences and Opportunities for Cross-fertilization

Abstract

Summary Adaptive designs involve preplanned rules for modifying an on‐going study based on accruing data. We compare the goals and methods of adaptation for trials and surveys, identify similarities and differences, and make recommendations for what types of adaptive approaches from one domain have high potential to be useful in the other. For example, clinical trials could benefit from recently developed survey methods for monitoring which groups have low response rates and intervening to fix this. Clinical trials may also benefit from more formal identification of the target population, and from using paradata (contextual information collected before or during the collection of actual outcomes) to predict participant compliance and retention and then to intervene to improve these. Surveys could benefit from stopping rules based on information monitoring, applying techniques from sequential multiple‐assignment randomized trial designs to improve response rates, prespecifying a formal adaptation protocol and including a data monitoring committee. We conclude with a discussion of the additional information, infrastructure and statistical analysis methods that are needed when conducting adaptive designs, as well as benefits and risks of adaptation.

Methodological Context and Communication on Data Quality: Discussion of Bailey (2023)

“…Taken as a whole, these developments provide a broad perspective on (a) a superpopulation model that leads to (2020), Citro (2014), Coffey et al (2023), Elliott and Valliant (2017), Harter et al (2016), Imbens and Rubin (2015), Lohr (2021), Lohr and Raghunathan (2017), Mahalanobis (1944), Pfeffermann (2015), Rao and Molina (2015), Rosenblum et al (2019), Tourangeau (2017), Tourangeau et al (2017), van Berkel et al (2020, Wagner et al (2020), Yang and Kim (2020), and references cited therein.…”

Some Open Questions on Multiple-Source Extensions of Adaptive-Survey Design Concepts and Methods

“…Most recently, continued technological advances, including increased computing power and the advent of formal literature on paradata (Couper 2000(Couper , 2017, have enabled adaptive and responsive survey designs (Groves and Heeringa 2006;Rosenblum et al 2019;Schouten et al 2017;Tourangeau et al 2017). Now, rather than offering a single data collection pathway to all sample units, available data collection features can be tailored to particular sample units to improve the quality and cost profiles for collected survey data.…”