Jim Weir and Stephen Senn are grateful to Novartis for providing funding for developing the macros.
|To carry out various approaches to analysing binary data including classic Mantel-Haenszel analysis but also, for example, the analysis of Normal-binomial mixtures using PROC NLMIXED®.
|To produce so-called forest plots whereby individual trials are represented by horizontal lines joining lower and upper confidence limits with a plotting symbol for the estimate and a final line and symbol for the overall meta-analytic summary
|To produce funnel plots. These plot the treatment estimate on the horizontal axis and the reciprocal of the standard error of the treatment estimate on the vertical axis.
|To produce radial or Galbraith plots as described in Statistics in Medicine, 1988.7,889-894. These plot the Z-scores, that is to say the ratio of estimated treatment effect to standard error, against the reciprocal of the standard error, where the latter is calculated as for a fixed effects analysis.
|To carry out classic fixed effects meta-analysis using inverse weighting by variances of treatment contrasts.
|To implement Lee's checks as described in Statistics in Medicine,1999,18,1973-1981.
|To produce QQ plots of estimated treatment effects by trial.
|To carry out random effects analysis using the approach of DerSimonian and Laird (DSL), Controlled Clinical Trials, 1986,7,177-188 and also using that of Hardy and Thompson(HT), Statistics in Medicine, 1996,15, 619-629.
|To examine the sensitivity of conclusions from random effects analysis to the magnitude of the random effects variance.