sm_chapter_25

sm_chapter_25 - CHAPTER 25 SOLUTIONS AND MINI-PROJECT NOTES...

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CHAPTER 25 SOLUTIONS AND MINI-PROJECT NOTES CHAPTER 25 META-ANALYSIS: RESOLVING INCONSISTENCIES ACROSS STUDIES EXERCISE SOLUTIONS 25.1 Whether or not studies are statistically significant depends very much on the sample size used. Vote- counting does not take that into account. 25.2 Studies should be included or excluded on the basis of quality and methodology, not on the basis of the results. Knowing the results might bias the selection; the temptation would be to include only successful ones. 25.3 a. They would like to make causal conclusions. b. Yes. They provide just as much information about the true size of the effect as the studies that did find significance. Excluding them would bias the results in favor of a strong effect. 25.4 Benefits 1, 2 and 4 are most relevant. The combined results may find useful treatments that were missed because of low power and may also detect patterns across studies that were not evident in individual studies. 25.5 If results are combined across studies, Simpson's Paradox could result. Confounding variables shouldn't be a problem because observational studies are excluded. Subtle differences in treatments by the same name could be a problem, such as the strength of a dose of chemotherapy where a larger dose could be too toxic. The file drawer problem could exist, so the treatments appear more effective than they are. Flawed original studies could produce erroneous summary results. A statistically significant treatment effect
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sm_chapter_25 - CHAPTER 25 SOLUTIONS AND MINI-PROJECT NOTES...

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