Adaptive design in surveys and clinical trials: similarities, differences and opportunities for cross‐fertilization
Michael Rosenblum,
Peter Miller,
Benjamin Reist,
Elizabeth A. Stuart,
Michael Thieme and
Thomas A. Louis
Journal of the Royal Statistical Society Series A, 2019, vol. 182, issue 3, 963-982
Abstract:
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.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://doi.org/10.1111/rssa.12438
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:182:y:2019:i:3:p:963-982
Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-985X
Access Statistics for this article
Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples
More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().