Analysis of Longitudinal Data with Irregular Observation Times


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Documentation for package ‘IrregLong’ version 0.4.0

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abacus.plot Create an abacus plot Creates an abacus plot, depicting visits per subject over time
addcensoredrows Add rows corresponding to censoring times to a longitudinal dataset
create.bootstrapped.dataset Create a single bootstrap sample for clustered data For clustered data, create a bootstrapped sample by sampling, with replacement, the same number of clusters as in the original dataset.
extent.of.irregularity Measures of extent of visit irregularity Provides visual and numeric measures of the extent of irregularity in observation times in a longitudinal dataset
iiw Given a proportional hazards model for visit intensities, compute inverse-intensity weights.
iiw.weights Compute inverse-intensity weights.
iiwgee Fit an inverse-intensity weighted GEE.
lagfn Create lagged versions the variables in data
Liang Fit a semi-parametric joint model
Liangint Fit a semi-parametric joint model, incorporating intercept estimation
mo Multiple outputation for longitudinal data subject to irregular observation.
outputation Create an outputted dataset for use with multiple outputation.