Ranking statistics of network meta-analysis such as SUCRA, MEANRANK, and probability of ranking are calculated by parametric bootstrap.
nmarank(x, B=20000, method="NH", ascending=TRUE, digits=3)The results of the ranking statistics of network meta-analysis are provided. Also, ranking probability plots are produced.
SUCRA: SUCRA estimates of individual treatment by parametric bootstrap.
MEANRANK: Mean rank estimates of individual treatment by parametric bootstrap.
Probability of ranking: Probability of ranking (best, 2nd, 3rd,..., worst) estimates of individual treatment by parametric bootstrap.
Output object of setup
Number of parametric bootstrap resampling (default: 20000)
Estimation and prediction method. NH: Noma-Hamura's improved REML-based methods (default). REML: The ordinary REML method. fixed: Fixed-effect model.
A logical value that specifies whether the ranking is defined by ascending or descending order. Set ascending=TRUE if a smaller value of the effect measure indicates a better outcome (e.g., mortality, frequency of adverse events, or other "harmful" outcomes). In this case, the treatment with the smallest estimate will be ranked first. Set ascending=FALSE if a larger value of the effect measure indicates a better outcome (e.g., cure rate, response rate, or other "beneficial" outcomes). In this case, the treatment with the largest estimate will be ranked first.
Number of decimal places
Chaimani, A., Higgins, J. P., Mavridis, D., Spyridonos, P., and Salanti, G. (2013). Graphical tools for network meta-analysis in STATA. PLoS One 8, e76654.
Salanti, G., Ades, A. E. and Ioannidis, J. P. (2011). Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: An overview and tutorial. Journal of Clinical Epidemiology 64, 163–171.
data(heartfailure)
hf2 <- setup(study=study,trt=trt,d=d,n=n,measure="OR",ref="Placebo",data=heartfailure)
nmarank(hf2)
nmarank(hf2, ascending=FALSE)
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