| Title |
Estimating Design Effect and Calculating Sample Size for Respondent-Driven Sampling Studies of Injection Drug Users in the United States
|
|---|---|
| Published in |
AIDS and Behavior, February 2012
|
| DOI | 10.1007/s10461-012-0147-8 |
| Pubmed ID | |
| Authors |
Cyprian Wejnert, Huong Pham, Nevin Krishna, Binh Le, Elizabeth DiNenno |
| Abstract |
Respondent-driven sampling (RDS) has become increasingly popular for sampling hidden populations, including injecting drug users (IDU). However, RDS data are unique and require specialized analysis techniques, many of which remain underdeveloped. RDS sample size estimation requires knowing design effect (DE), which can only be calculated post hoc. Few studies have analyzed RDS DE using real world empirical data. We analyze estimated DE from 43 samples of IDU collected using a standardized protocol. We find the previous recommendation that sample size be at least doubled, consistent with DE = 2, underestimates true DE and recommend researchers use DE = 4 as an alternate estimate when calculating sample size. A formula for calculating sample size for RDS studies among IDU is presented. Researchers faced with limited resources may wish to accept slightly higher standard errors to keep sample size requirements low. Our results highlight dangers of ignoring sampling design in analysis. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 75% |
| Canada | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Chile | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 148 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 21% |
| Student > Ph. D. Student | 21 | 14% |
| Student > Master | 20 | 13% |
| Student > Bachelor | 10 | 7% |
| Student > Postgraduate | 8 | 5% |
| Other | 24 | 16% |
| Unknown | 37 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 36 | 24% |
| Social Sciences | 23 | 15% |
| Nursing and Health Professions | 15 | 10% |
| Psychology | 7 | 5% |
| Economics, Econometrics and Finance | 5 | 3% |
| Other | 23 | 15% |
| Unknown | 42 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 October 2018.
All research outputs
#3,157,275
of 24,739,153 outputs
Outputs from AIDS and Behavior
#451
of 3,642 outputs
Outputs of similar age
#25,859
of 260,452 outputs
Outputs of similar age from AIDS and Behavior
#6
of 50 outputs
Altmetric has tracked 24,739,153 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,642 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done well, scoring higher than 87% of its peers.
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