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Data Sources for Health Economics and Outcomes Research
Published in Demissie Alemayehu, Joseph C. Cappelleri, Birol Emir, Kelly H. Zou, Statistical Topics in Health Economics and Outcomes Research, 2017
Kelly H. Zou, Christine L. Baker, Joseph C. Cappelleri, Richard B. Chambers
Meta-analysis refers to the practice of applying statistical methods to combine and quantify the outcomes of a series of studies in a single pooled analysis. It is part of a quantitative systematic overview. The Cochrane Consumer Network (2017) states the following: “A systematic review summarizes the results of available carefully designed health care studies (controlled trials) and provides a high level of evidence on the effectiveness of health care interventions. Judgments may be made about the evidence and inform recommendations for health care to summarize the results of available carefully designed health care studies (controlled trials) and provides a high level of evidence on the effectiveness of health care interventions. Judgments may be made about the evidence and inform recommendations for health care.” Additionally, it employs specific analytic methods for combining pertinent quantitative results from multiple selected studies to develop an overall estimate with its accompanying precision. The Cochrane Library (2017) provides a set of training items about the foundational concepts associated with both systematic review and meta-analysis.
Epidemiological Approaches to Studying Cancer I
Published in Peter G. Shields, Cancer Risk Assessment, 2005
Pooled analysis: In a pooled analysis, the investigator conducts a combined analysis of a collection of studies, after standardization of the studies to allow exposure variables to be combined. Unlike in meta-analysis, in pooled analysis the investigator uses the primary data (73). A recent article compared the results of a meta-analysis and a pooled analysis of studies of sinonasal cancer among wood workers and proposed criteria for whether a pooled analysis of raw data or a meta-analysis should be carried out (74).
Effect of hypoxia-inducible factor-prolyl hydroxylase inhibitors on anemia in patients with CKD: a meta-analysis of randomized controlled trials including 2804 patients
Published in Renal Failure, 2020
Bin Wang, Qing Yin, Yu-Chen Han, Min Wu, Zuo-Lin Li, Yan Tu, Le-ting Zhou, Qing Wei, Hong Liu, Ri-Ning Tang, Jing-Yuan Cao, Lin-Li Lv, Bi-Cheng Liu
Mean differences (MDs) or standard mean difference (SMD) as the effect size were used to pool results from all studies that reported changes in hemoglobin, hepcidin, ferritin, transferrin, TIBC, serum iron, and TSAT. Risk Ratio (RR) served as the effect size for the pooled analysis of adverse events. A random-effect model was used for pooled analysis to account for heterogeneity across studies. The heterogeneity between studies was assessed by using the Cochran Q test and quantified by I2 statistic. Potential heterogeneity was investigated by comparing summary results obtained from subgroups of studies stratified by intervention in the control group, dialysis status, and follow-up duration. Publication bias was assessed with Egger’s test and Begg’s test. All statistical analyses were performed with the Meta for package in R (x64, version 3.3.3, R Foundation for Statistical Computing, Vienna, Austria).