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Presented at CRC course held at King Fahad Medical City, Riyadh on 13 February 2020 by Professor Omar Hasan Kasule Sr. MB ChB (MUK), MPH (Harvard), DrPH (Harvard), Member of the Institutional Review Board, King Fahad Medical City
DEFINITION OF META-ANALYSIS
• Meta-analysis refers to methods used to combine data from more than one study to produce a quantitative summary statistic.
• Meta-analysis enables computation of an effect estimate for a larger number of study subjects thus enabling picking up statistical significance that would be missed if the analysis were based on small individual studies.
• Meta-analysis also enables the study of variation across several population subgroups since it involves several individual studies carried out in various countries and populations.
PROCESS OF META-ANALYSIS - 1
• Criteria must be set for what articles to include or exclude.
• Information is abstracted from the articles on a standardized data abstract form with the standard outcome, exposure, confounder, or effect modifying variables.
• The first step is to display the effect measures with each article with their 95% confidence limits to get a general idea of their distribution before proceeding to compute summary measures.
PROCESS OF META-ANALYSIS - 2
• The summary effect measure, OR or 
, is computed from the effect measures of individual studies using weighted logistic regression or computing a MH weighted average in which the weight of each measure is the inverse of its precision i.e. 1/(se)2.
• In both the logistic or MH procedures, each study is treated as a stratum.
• The combined effect measure is then statistically adjusted for confounding, selection, and misclassification biases.
• Tests of homogeneity can be carried out before computing the summary effect measure.
• Sensitivity analysis is undertaken to test the robustness of the combined effect measure.