Title |
Data extraction for complex meta-analysis (DECiMAL) guide
|
---|---|
Published in |
Systematic Reviews, December 2016
|
DOI | 10.1186/s13643-016-0368-4 |
Pubmed ID | |
Authors |
Hugo Pedder, Grammati Sarri, Edna Keeney, Vanessa Nunes, Sofia Dias |
Abstract |
As more complex meta-analytical techniques such as network and multivariate meta-analyses become increasingly common, further pressures are placed on reviewers to extract data in a systematic and consistent manner. Failing to do this appropriately wastes time, resources and jeopardises accuracy. This guide (data extraction for complex meta-analysis (DECiMAL)) suggests a number of points to consider when collecting data, primarily aimed at systematic reviewers preparing data for meta-analysis. Network meta-analysis (NMA), multiple outcomes analysis and analysis combining different types of data are considered in a manner that can be useful across a range of data collection programmes. The guide has been shown to be both easy to learn and useful in a small pilot study. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 12 | 38% |
Canada | 3 | 9% |
United States | 2 | 6% |
Mexico | 1 | 3% |
Spain | 1 | 3% |
Belgium | 1 | 3% |
Ireland | 1 | 3% |
France | 1 | 3% |
Lebanon | 1 | 3% |
Other | 1 | 3% |
Unknown | 8 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 16 | 50% |
Scientists | 10 | 31% |
Practitioners (doctors, other healthcare professionals) | 4 | 13% |
Science communicators (journalists, bloggers, editors) | 2 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
Switzerland | 1 | <1% |
Unknown | 123 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 27 | 22% |
Researcher | 18 | 14% |
Student > Master | 12 | 10% |
Student > Bachelor | 11 | 9% |
Student > Doctoral Student | 10 | 8% |
Other | 20 | 16% |
Unknown | 27 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 25 | 20% |
Agricultural and Biological Sciences | 15 | 12% |
Psychology | 10 | 8% |
Social Sciences | 7 | 6% |
Biochemistry, Genetics and Molecular Biology | 5 | 4% |
Other | 27 | 22% |
Unknown | 36 | 29% |