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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Estimation of treatment preference effects in clinical trials when some participants are indifferent to treatment choice
|
|---|---|
| Published in |
BMC Medical Research Methodology, February 2017
|
| DOI | 10.1186/s12874-017-0304-x |
| Pubmed ID | |
| Authors |
Stephen D. Walter, Robin M. Turner, Petra Macaskill, Kirsten J. McCaffery, Les Irwig |
| Abstract |
In the two-stage randomised trial design, a randomly sampled subset of study participants are permitted to choose their own treatment, while the remaining participants are randomised to treatment in the usual way. Appropriate analysis of the data from both arms of the study allows investigators to estimate the impact on study outcomes of treatment preferences that patients may have, in addition to evaluating the usual direct effect of treatment. In earlier work, we showed how to optimise this design by making a suitable choice of the proportion of participants who should be assigned to the choice arm of the trial. However, we ignored the possibility of some participants being indifferent to the treatments under study. In this paper, we extend our earlier work to consider the analysis of two-stage randomised trials when some participants have no treatment preference, even if they are assigned to the choice arm and allowed to choose. We compare alternative characterisations of the response profiles of the indifferent or undecided participants, and derive estimates of the treatment and preference effects on study outcomes. We also present corresponding test statistics for these parameters. The methods are illustrated with data from a clinical trial contrasting medical and surgical interventions. Expressions are obtained to estimate and test the impact of treatment choices on study outcomes, as well as the impact of the actual treatment received. Contrasts are defined between patients with stated treatment preferences and those with no preference. Alternative assumptions concerning the outcomes of undecided participants are described, and an approach leading to unbiased estimation and testing is identified. Use of the two-stage design can provide important insights into determinants of study outcomes that are not identifiable with other designs. The design can remain attractive even in the presence of participants with no stated treatment preference. |
X Demographics
The data shown below were collected from the profiles of 15 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 Kingdom | 7 | 47% |
| India | 1 | 7% |
| Spain | 1 | 7% |
| Canada | 1 | 7% |
| Unknown | 5 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 53% |
| Scientists | 6 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 19% |
| Researcher | 2 | 10% |
| Professor | 2 | 10% |
| Student > Doctoral Student | 1 | 5% |
| Student > Master | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 10 | 48% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 3 | 14% |
| Medicine and Dentistry | 3 | 14% |
| Arts and Humanities | 1 | 5% |
| Psychology | 1 | 5% |
| Mathematics | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 10 | 48% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 23 February 2017.
All research outputs
#3,715,459
of 23,577,654 outputs
Outputs from BMC Medical Research Methodology
#558
of 2,081 outputs
Outputs of similar age
#65,415
of 311,574 outputs
Outputs of similar age from BMC Medical Research Methodology
#9
of 35 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,081 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 311,574 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.