HRP 206: Meta-research: Appraising Research Findings, Bias, and Meta-analysis (CHPR 206, MED 206, STATS 211)
Open to graduate, medical, and undergraduate students. Appraisal of the quality and credibility of research findings; evaluation of sources of bias. Meta-analysis as a quantitative (statistical) method for combining results of independent studies. Examples from medicine, epidemiology, genomics, ecology, social/behavioral sciences, education. Collaborative analyses. Project involving generation of a meta-research project or reworking and evaluation of an existing published meta-analysis. Prerequisite: knowledge of basic statistics.
Terms: Win
| Units: 3
Instructors:
Ioannidis, J. (PI)
;
Michael, H. (TA)
HRP 265: Methods for Network Meta-Analysis
The course will cover the area of network meta-analysis, a technique used to compare treatments that have not been compared directly to each other, but are included in a "network" of randomized trials that allows inferences to be made based on indirect comparisons. In traditional meta-analysis all included studies compare the same intervention with the same comparator. Network meta-analysis extends this concept by including multiple pair-wise comparisons across a range of interventions and provides estimates of relative treatment effects between all interventions in the network. This technique is being increasingly used in evidence-based medicine, health technology assessments and policy making. nnRecommended preparation: HEP 206, and at least 2 quarters of biostatistics and one of epidemiology, including clinical research design. Familiarity with logistic and linear regression modeling required.
Terms: Spr
| Units: 2
Instructors:
Goodman, S. (PI)
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