bayes.nmr |
Fit Bayesian Network Meta-Regression Models |
bayes.parobs |
Fit Bayesian Inference for Meta-Regression |
bmeta_analyse |
bmeta_analyze supersedes the previous two functions: bayes.parobs, bayes.nmr |
bmeta_analyze |
bmeta_analyze supersedes the previous two functions: bayes.parobs, bayes.nmr |
cholesterol |
26 double-blind, randomized, active, or placebo-controlled clinical trials on patients with primary hypercholesterolemia sponsored by Merck & Co., Inc., Kenilworth, NJ, USA. |
coef.bsynthesis |
get the posterior mean of fixed-effect coefficients |
fitted.bayes.parobs |
get fitted values |
fitted.bayesnmr |
get fitted values |
hpd |
get the highest posterior density (HPD) interval |
hpd.bayes.parobs |
get the highest posterior density (HPD) interval or equal-tailed credible interval |
hpd.bayesnmr |
get the highest posterior density (HPD) interval |
metapack |
metapack: a package for Bayesian meta-analysis and network meta-analysis |
model.comp |
compute the model comparison measures: DIC, LPML, or Pearson's residuals |
model.comp.bayes.parobs |
compute the model comparison measures |
model.comp.bayesnmr |
get compute the model comparison measures |
ns |
helper function encoding trial sample sizes in formulas |
plot.bayes.parobs |
get goodness of fit |
plot.bayesnmr |
get goodness of fit |
plot.sucra |
plot the surface under the cumulative ranking curve (SUCRA) |
print.bayes.parobs |
Print results |
print.bayesnmr |
Print results |
sucra |
get surface under the cumulative ranking curve (SUCRA) |
sucra.bayesnmr |
get surface under the cumulative ranking curve (SUCRA) |
summary.bayes.parobs |
'summary' method for class "'bayes.parobs'" |
summary.bayesnmr |
Summarize results |
TNM |
Triglycerides Network Meta (TNM) data |