Man pages for metapack
Bayesian Meta-Analysis and Network Meta-Analysis
| bayes_nmr | Fit Bayesian Network Meta-Regression Models |
| bayes_parobs | Fit Bayesian Inference for Meta-Regression |
| bmeta_analyze | bmeta_analyze supersedes the previous two functions:... |
| cholesterol | 26 double-blind, randomized, active, or placebo-controlled... |
| coef.bsynthesis | get the posterior mean of fixed-effect coefficients |
| fitted.bayesnmr | get fitted values |
| fitted.bayesparobs | get fitted values |
| hpd | get the highest posterior density (HPD) interval |
| hpd.bayesnmr | get the highest posterior density (HPD) interval |
| hpd.bayesparobs | get the highest posterior density (HPD) interval or... |
| metapack | metapack: a package for Bayesian meta-analysis and network... |
| model_comp | compute the model comparison measures: DIC, LPML, or... |
| model_comp.bayesnmr | get compute the model comparison measures |
| model_comp.bayesparobs | compute the model comparison measures |
| ns | helper function encoding trial sample sizes in formulas |
| plot.bayesnmr | get goodness of fit |
| plot.bayesparobs | get goodness of fit |
| plot.sucra | plot the surface under the cumulative ranking curve (SUCRA) |
| print.bayesnmr | Print results |
| print.bayesparobs | Print results |
| sucra | get surface under the cumulative ranking curve (SUCRA) |
| sucra.bayesnmr | get surface under the cumulative ranking curve (SUCRA) |
| summary.bayesnmr | 'summary' method for class "'bayesnmr'" |
| summary.bayesparobs | 'summary' method for class "'bayesparobs'" |
| TNM | Triglycerides Network Meta (TNM) data |
