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Tag Archives: Systematic overviews
Recommended: Bayesian meta-analysis of two proportions in random control trials
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I got a question about Bayesian meta-analysis and found this nice teaching example. I’m not sure if the graphs are from the R package bayesmeta, but it looks like it. Continue reading
PMean: Are systematic overviews reliable?
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Dear Professor Mean, I’m helping a student with a piece of work and he described systematic reviews as being reliable. I’m troubled by this on a number of fronts. Continue reading
Recommended: Published methodological quality of randomized controlled trials does not reflect the actual quality assessed in protocols
When evaluating a series of research articles, you often have to assess the quality of the individual papers based on the type of blinding, for example. What do you do if the paper does not discuss these items? I have usually advocated a “no news is bad news policy.” If a paper does not mention blinding, assume that no blinding was done. It seems reasonable, but the paper by Mhaskar et al provides empirical evidence that sometimes authors leave out information that would strengthen the credibility of their study. A similar paper is at https://www.ncbi.nlm.nih.gov/pubmed/22424985 Continue reading
PMean: So you’re thinking about a systematic overview
If you are designing a systematic overview, you should talk to a statistician early in the process. There are lots of little things that you can do to make your research more rigorous. Here is a broad overview of these issues. Continue reading
PMean: Meta-analysis of ordinal data
Dear Professor Mean, I would like to conduct a meta-analysis of several studies. The data in these studies were evaluated using an ordinal scoring system coded as 0,1,2,3. How to I combine the results of these studies? Continue reading
Recommended: In search of justification for the unpredictability paradox
This is a commentary on a 2011 Cochrane Review that found substantial differences between studies that were adequately randomized and those that were not adequately randomized. The direction of the difference was not predictable, however, meaning that there was not a consistent bias on average towards overstating the treatment effect or a consistent bias on average towards understating the treatment effect. This leads the authors of the Cochrane review to conclude that “the unpredictability of random allocation is the best protection against the unpredictability of the extent to which non-randomised studies may be biased.” The authors of the commentary provide a critique of this conclusion on several grounds. Continue reading
Recommended: Row over breast cancer screening shows that scientists bring some subjectivity into their work.
This is a classic reference that reminds us that even with all the objective methods developed for systematic overviews, there is still a core of choices that are largely subjective. Continue reading