EvidenceSynthesis1.1.0 package

Approximate Bayesian posterior for hierarchical Normal model

Approximate a likelihood function

Approximate simple Bayesian posterior

Bias Correction with Inference

Build a list of references that map likelihood names to integer labels...

Compute a Bayesian random-effects meta-analysis

Compute the point estimate and confidence interval given a likelihood ...

Compute a fixed-effect meta-analysis

Compute a Bayesian random-effects hierarchical meta-analysis

Construct DataModel objects from approximate likelihood or profile l...

Create likelihood approximations from individual-trajectory data

Create SCCS simulation settings

Create simulation settings

A custom function to approximate a log likelihood function

Detect the type of likelihood approximation based on the data format

EvidenceSynthesis: Synthesizing Causal Evidence in a Distributed Resea...

Compute source-specific biases and bias-corrected estimates from hiera...

Fit Bias Distribution

Generate settings for the Bayesian random-effects hierarchical meta-an...

Cubic Hermite interpolation using both values and gradients to approxi...

Load the Cyclops dynamic C++ library for use in Java

Plot bias correction inference

Plot bias distributions

Plot covariate balances

Plot empirical null distributions

Plot the likelihood approximation

Plot MCMC trace

Create a forest plot

Plot MCMC trace for individual databases

Plot posterior density per database

Plot posterior density

Plot the propensity score distribution

Prepare to plot the propensity score distribution

Prepare SCCS interval data for pooled analysis

Fit Bias Distribution Sequentially or in Groups

Simulate survival data across a federated data network, with negative ...

Simulate survival data for multiple databases

The skew normal function to approximate a log likelihood function

Utility function to summarize MCMC samples (posterior mean, median, HD...

Determine if Java virtual machine supports Java