Package index • JointODE

Model Fitting

Core functionality for fitting joint ODE models combining survival and longitudinal data

JointODE(): Joint Modeling of Longitudinal and Survival Data Using ODEs
MarginalODE(): Marginal Second-Order ODE Parameter Estimation

Model Inspection

Extract and examine fitted model components and parameters

coef(<JointODE>): Extract Model Coefficients
coef(<MarginalODE>): Extract Model Coefficients
logLik(<JointODE>): Extract Log-Likelihood
logLik(<MarginalODE>): Extract Log-Likelihood
vcov(<JointODE>): Extract Variance-Covariance Matrix
vcov(<MarginalODE>): Extract Variance-Covariance Matrix
predict(<JointODE>): Predict Method for JointODE Objects
predict(<MarginalODE>): Predict Method for MarginalODE Objects

Model Summary & Display

Summarize and display model results with statistical inference

print(<summary.MarginalODE>): Print Summary of MarginalODE Model
summary(<JointODE>): Summary of JointODE Model
summary(<MarginalODE>): Summary of MarginalODE Model
plot(<JointODE>): Plot Method for JointODE Objects
print(<JointODE>): Print JointODE Model
print(<MarginalODE>): Print MarginalODE Model

Advanced Methods

Computational methods for sensitivity analysis and optimization

Data & Simulation

Tools for simulating joint ODE data and example datasets

sim: Example Dataset for Joint ODE Model
simulate(): Simulate Data from a Joint Ordinary Differential Equation Model

Re-exports

Surv: Re-exported from survival