- Framework of problems / Rigourous
- Data extraction errors and double counting
- Missing binary data extraction challenges from Cochrane reviews in mental health and Campbell reviews with implications for empirical research
Ref ID | 658 |
First Author | L. M. Spineli |
Journal | RESEARCH SYNTHESIS METHODS |
Year Of Publishing | 2017 |
URL | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/jrsm.1268?download=true |
Keywords |
Cochrane Campbell Missing data Error General medical |
Problem(s) |
Failure to address missing outcome data in analyses Data extraction errors and double counting |
Number of systematic reviews included | 113 |
Summary of Findings | More than half of 113 eligible Cochrane meta‐analyses were evaluated as “unclearly” extracted (53%); 42 (37%) were “unacceptably” extracted and only 11 (10%) were “acceptably” extracted. The direct implication of “unclear” extraction is unnecessary inflation in uncertainty of estimated odds ratio irrespective of method used to address missingness. |
Did the article find that the problem(s) led to qualitative changes in interpretation of the results? | No |
Are the methods of the article described in enough detail to replicate the study? | No |