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Meta-analysis: odds ratio

Command:Statistics
Next selectMeta-analysis
Next selectOdds ratio

Description

For a short overview of meta-analysis in MedCalc, see Meta-analysis: introduction.

MedCalc uses the Mantel-Haenszel method (Mantel & Haenszel, 1959) for calculating the weighted pooled odds ratio under the fixed effects model. Next the heterogeneity statistic is incorporated to calculate the summary odds ratio under the random effects model (DerSimonian & Laird, 1986).

How to enter data

The data of different studies can be entered as follows in the spreadsheet:

Odds ratio meta-analysis - how to enter data

In this example, in a first study 73 cases were treated with an active substance and of these, 15 had a positive outcome. 23 cases received a placebo and 3 of these had a positive outcome. On the next rows of the spreadsheet follow the data of 4 other studies.

Required input

The dialog box for "Meta-analysis: odds ratio" can then be completed as follows:

Odds ratio meta-analysis - dialog box

Studies: a variable containing an identification of the different studies.

Intervention groups

Control groups

Filter

A filter to include only a selected subgroup of studies in the meta-analysis.

Filter: a filter to include only a selected subgroup of cases in the graph.

Options

Results

Odds ratio meta-analysis - results

The program lists the results of the individual studies: number of positive cases, total number of cases, and the odds ratio with 95% CI.

The pooled odds ratio with 95% CI is given both for the Fixed effects model and the Random effects model. If the value 1 is not within the 95% CI, then the Odds ratio is statistically significant at the 5% level (P<0.05).

The random effects model will tend to give a more conservative estimate (i.e. with wider confidence interval), but the results from the two models usually agree where there is no heterogeneity. See Meta-analysis: introduction for interpretation of the heterogeneity statistics Cohran's Q and I2. When heterogeneity is present the random effects model should be the preferred model.

See Meta-analysis: introduction for interpretation of the different publication bias tests.

Note that when a study reports no events (or all events) in both intervention and control groups the study provides no information about relative probability of the event and is automatically omitted from the meta-analysis (Higgins & Green, 2011).

Forest plot

The results of the different studies, with 95% CI, and the overall effect with 95% CI are shown in a forest plot:

Odds ratio meta-analysis - forest plot

Note that the Odds ratios with 95% CI are drawn on a logarithmic scale.

Literature

See also