Article type
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Abstract
Objectives:
The Cochrane Statistical Methods Group has developed a series of workshops addressing statistical guidelines as formulated in the Cochrane Handbook for Systematic Reviews of Interventions. This workshop will provide review authors with the knowledge of issues surrounding meta-analysis of binary and continuous outcomes.
Description:
Binary and continuous data are commonly encountered in health care. Pooling intervention effects from binary and continuous data presents unique methodological issues; some of these issues will be discussed in this workshop. A brief introduction to meta-analysis of binary and continuous outcomes will be included, consisting of data extraction (extraction of event frequencies and/or effect estimates, and the extraction of standard deviations from standard errors, confidence intervals, test statistics and P values); and dealing with outcomes measured on different scales. More complex issues will be discussed, including options for pooling estimates of intervention effect when a mix of results from analyses using change from baseline and final values have been reported; and use of the generic inverse variance method. Issues will be illustrated by examples.
The Cochrane Statistical Methods Group has developed a series of workshops addressing statistical guidelines as formulated in the Cochrane Handbook for Systematic Reviews of Interventions. This workshop will provide review authors with the knowledge of issues surrounding meta-analysis of binary and continuous outcomes.
Description:
Binary and continuous data are commonly encountered in health care. Pooling intervention effects from binary and continuous data presents unique methodological issues; some of these issues will be discussed in this workshop. A brief introduction to meta-analysis of binary and continuous outcomes will be included, consisting of data extraction (extraction of event frequencies and/or effect estimates, and the extraction of standard deviations from standard errors, confidence intervals, test statistics and P values); and dealing with outcomes measured on different scales. More complex issues will be discussed, including options for pooling estimates of intervention effect when a mix of results from analyses using change from baseline and final values have been reported; and use of the generic inverse variance method. Issues will be illustrated by examples.