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Improving Reproducibility of Respondent Driven Sampling through Adaptive Design

Award Number: R01AG060936
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 02/15/2019
PERIOD OF PERFORMANCE END DATE: 12/31/2025

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Improving Reproducibility of Respondent Driven Sampling through Adaptive Design - Respondent driven sampling (RDS) is a recruitment method for hard-to-sample populations that are rare in number and/or elusive due to highly-stigmatized or illicit behaviors. For these groups, traditional probability sampling rarely offers feasibility, because it requires prohibitively high screening costs to locate eligible persons, and, even when eligible persons are located, their desire to hide produces false negatives. Based on the premise that people of similar traits form some type of social networks, RDS exploits the existing networks for recruitment and has been applied to numerous studies. What sets RDS apart from traditional sampling is that the recruitment process is mostly controlled by participants themselves through their chain- referral that asks participants to recruit other eligible persons from their networks. The use of organic social networks for sampling is an innovative feature of RDS. This, however, comes with one major challenge. In order to capitalize on RDS, participants need to cooperate with recruitment requests. Because of noncooperation, the sample may stop growing in size, resulting in a project overrun. However, the lack of attention to this noncooperation process in the literature makes RDS data collection progress extremely difficult to predict at the design stage, and when faces with undesirable (and often unexpected) challenges, researchers are forced to make unplanned design changes (e.g., offering larger incentives) on the spur of the moment in hopes of making RDS “work”. Additionally, noncooperation leads to a violation of a critical assumption of RDS inferences. In sum, the current practice of RDS lacks operational and statistical reproducibility, making its scientific integrity questionable. This study attempts to improve reproducibility of RDS by proposing Adaptive-RDS (A-RDS) as a design framework and to provide practical tools on which researchers rely for successful implementation of RDS and by developing A-RDS specific design guidelines and software that will allow monitoring RDS data collection progress and improve inferences that closely mirror the true data generation process. Under A-RDS, we will plan design adaptation strategies, including indicators and rules for adaptations prior to the data collection. During the field work, instead of assuming the same recruitment cooperation patterns across participants, we will predict individual-level cooperation propensities from incoming data and tailor the number and type of coupons for each participant received based on the pre-specified rules. For doing so, data collection progress will be closely monitored and used for making adaptation decisions. In particular, this approach is empirically applied to PWID studies to provide data for addressing rapidly escalated issues with opioid use. By providing a practical yet data-driven, rule-based tool to the research community, the proposed study will boost researchers' control on the operations of RDS, leading to not only improved reproducibility but also increased chances of meeting critical assumptions in RDS required for valid inferences.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $0 )
2025	2023	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE, SUITE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	000	5	1/14/2025	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2023 ( Subtotal = $246,647 )
2023	2023	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON STREET	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	001	5	1/26/2023	SUPPLEMENT FOR EXPANSION	$27,670
2023	2023	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON STREET	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	000	5	1/20/2023	NON-COMPETING CONTINUATION	$218,977
														Subtotal = $246,647

Issue Date FY: 2022 ( Subtotal = $481,641 )
2022	2022	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	001	4	5/4/2022	NON-COMPETING CONTINUATION	$46,907
2022	2022	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	002	4	8/24/2022	SUPPLEMENT FOR EXPANSION	$12,579
2022	2022	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	000	4	1/18/2022	NON-COMPETING CONTINUATION	$422,155
														Subtotal = $481,641

Issue Date FY: 2021 ( Subtotal = $475,527 )
2021	2021	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	000	3	3/18/2021	NON-COMPETING CONTINUATION	$475,527
														Subtotal = $475,527

Issue Date FY: 2020 ( Subtotal = $489,634 )
2020	2020	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	001	2	1/22/2020	NON-COMPETING CONTINUATION	$48,965
2020	2020	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	000	2	12/20/2019	NON-COMPETING CONTINUATION	$440,669
														Subtotal = $489,634

Issue Date FY: 2019 ( Subtotal = $525,255 )
2019	2019	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	000	1	2/15/2019	NEW	$489,440
2019	2019	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON ST	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	001	1	8/10/2019	NEW	$35,815
														Subtotal = $525,255

Grand Total All Awards = $2,218,704

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Improving Reproducibility of Respondent Driven Sampling through Adaptive Design

Award Number: R01AG060936

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 02/15/2019

PERIOD OF PERFORMANCE END DATE: 12/31/2025

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