Description Usage Arguments Value References Examples
Based on the method proposed by Dormuth et al, 2016, the function estimates traditional 95% confidence intervals and intrinsic confidence intervals for combined effect estimates (OR) in meta-analysis. It also returns an estimate of heterogeneity accross studies as well as Isq statistics in random meta-analysis.
1 | metalr_or(idata, refval, num_iter, increm, method = "random")
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idata |
A dataframe of 4 columns for cases control pairs for treatments |
refval |
The reference value for the log of the alternate hypothesis |
num_iter |
The number of iterations or steps from the alternate hypothesis |
increm |
The quantity of increments of the refval upto the number of iterations |
method |
The meta-analytic method i.e. fixed or random effect method. |
Total_RE : A dataframe of total effect estimate from meta analysis, the 95% CIs and intrinsic CIs.
Tausq : Measure of heterogeneity between the studies used in the meta-analysis in random effect meta-analysis.
Isq : The I^2 statistics
meta_results : Dataframe effect estimates from all the studies, the 95% confidence limits and the 95% intrinsic confidence limits.
Dormuth, Colin R., Kristian B. Filion, and Robert W. Platt. "Likelihood ratio meta-analysis: New motivation and approach for an old method." Contemporary clinical trials 47 (2016): 259-265.
1 2 3 4 5 6 | ## Not run:
# statin potency and acute kidney injury data
data("statindata")
metalr_or(idata=statindata[,2:5],refval=0,num_iter=3000,increm=0.001,method = "random")
## End(Not run)
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