Joint Modelling for Meta-Analytic (Multi-Study) Data


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Documentation for package ‘joineRmeta’ version 0.1.2

Help Pages

confint.jointmeta1SE Extract confidence intervals
fixef.jointmeta1 Extract fixed effects
formula.jointmeta1 Extract formulae from joint model fit
JMfits Study specific joint model fits using the JM package
JMfits2 Study specific joint model fits using the JM package
joineRfits Study specific joint model fits using the joineR package
joineRfits2 Study specific joint model fits using the joineR package
jointmeta1 One stage joint meta function
jointmeta1.object Fitted 'jointmeta1' object
jointmeta1SE.object A 'jointmeta1SE' object
jointmeta2 Function to pool joint model fits in two stage MA
jointmetaplot Produce plots of longitudinal and survival outcomes
jointmetaplotall Arrange study plots into a grid
jointmetaSE Bootstrapping function to obtain standard errors for jointmeta1 fit
onestage0 One stage jointmeta1 fit and bootstrapped standard errors
onestage1 One stage jointmeta1 fit and bootstrapped standard errors
onestage2 One stage jointmeta1 fit and bootstrapped standard errors
onestage3 One stage jointmeta1 fit and bootstrapped standard errors
onestage4 One stage jointmeta1 fit and bootstrapped standard errors
print.jointmeta1 Print function for 'jointmeta1' objects
print.jointmeta1SE Print function for 'jointmeta1SE' objects
rancov Function to extract the estimated covariance matrices for the random effects specified in the model
ranef.jointmeta1 Function to extract estimated random effects
removeafter Code to remove longitudinal information recorded after survival outcome
simdat Simulated joint longitudinal and survival dataset containing 5 studies
simdat2 Simulated joint longitudinal and survival dataset containing 3 studies
simdat3 Simulated joint longitudinal and survival dataset containing 5 studies
simjointmeta Simulation of multi-study joint data
summary.jointmeta1 Summary function for jointmeta1
tojointdata Function to change multi-study data into jointdata format
vcov.jointmeta1SE Extract the variance covariance matrix from the bootstrapped results