Missing Data and Measurement Error Modelling in INLA
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Documentation for package ‘inlamemi’ version 1.0.0
Help Pages
| extract_random_effects | Extract random effects from formula |
| extract_variables_from_formula | Extract and group variables from formulas |
| fit_inlamemi | Fit model for measurement error and missing data in INLA |
| framingham | Framingham heart study data |
| inla_survival_families | List the survival likelihoods in INLA |
| make_inlamemi_control.family | Make "control.family" argument for passing to the "inla" function |
| make_inlamemi_families | Make vector of likelihood families |
| make_inlamemi_formula | Make formula for measurement error and missing data model |
| make_inlamemi_scaling_vector | Construct scaling vector to scale the precision of correctly observed observations |
| make_inlamemi_stacks | Make data stacks for joint model specification in INLA |
| mar_data | Simulated data with observation missing at random (MAR) |
| nhanes_survival | Survival data with repeated systolic blood pressure measurements |
| plot.inlamemi | Plot model summary |
| print.summary.inlamemi | Summary method for inlamemi |
| show_data_structure | Visualize the model data structure as matrices |
| simple_data | Simple simulated data |
| simplify_inlamemi_model_summary | Simplify the "raw" model summary for printing and plotting |
| summary.inlamemi | Summary method for inlamemi |
| two_error_data | Simulated data with two covariates with classical measurement error |