Sensitivity Analysis for Irregular Assessment Times
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Documentation for package ‘SensIAT’ version 0.2.0
Help Pages
| add_class | Adds an S3 class to an object |
| add_terminal_observations | Add Terminal Observations to a Dataset |
| autoplot.SensIAT_fulldata_jackknife_results | Plot for estimated treatment effect for 'SensIAT_fulldata_jackknife_results' objects |
| autoplot.SensIAT_fulldata_model | Plot for estimated treatment effect for 'SensIAT_fulldata_model' objects |
| autoplot.SensIAT_withingroup_jackknife_results | Plot estimates at given times for 'SensIAT_withingroup_jackknife_results' objects |
| autoplot.SensIAT_within_group_model | Plot a 'SensIAT_within_group_model' object |
| compute_influence_terms | Compute Influence Terms |
| compute_influence_terms.default | Compute Influence Terms |
| compute_influence_terms.SensIAT::Single-index-outcome-model | Compute Influence Terms |
| fit_SensIAT_fulldata_model | Produce fitted model for group (treatment or control) |
| fit_SensIAT_within_group_model | Produce fitted model for group (treatment or control) |
| jackknife | Perform Jackknife resampling on an object. |
| jackknife.SensIAT_fulldata_model | Perform Jackknife resampling on an object. |
| jackknife.SensIAT_within_group_model | Perform Jackknife resampling on an object. |
| pcoriaccel_estimate_pmf | Directly estimate the probability mass function of Y. |
| pcoriaccel_evaluate_basis | Compiled version of 'evaluate_basis()' function |
| pcoriaccel_evaluate_basis_mat | Compiled version of 'evaluate_basis()' function (matrix version) |
| predict.SensIAT_fulldata_model | Predict mean and variance of the outcome for a 'SensIAT' within-group model |
| predict.SensIAT_within_group_model | Predict mean and variance of the outcome for a 'SensIAT' within-group model |
| SensIAT_example_data | SensIAT Example Data |
| SensIAT_example_fulldata | SensIAT Example Data |
| SensIAT_fit_marginal_model | Title |
| SensIAT_jackknife | Estimate response with jackknife resampling |
| SensIAT_jackknife_fulldata | Estimate response with jackknife resampling |
| SensIAT_prepare_data | Prepare data for SensIAT analysis |
| SensIAT_sim_outcome_modeler | Outcome Modeler for 'SensIAT' Single Index Model. |
| SensIAT_sim_outcome_modeler_fbw | Outcome Modeler for 'SensIAT' Single Index Model. |
| SensIAT_sim_outcome_modeler_mave | Single Index Model using MAVE and Optimizing Bandwidth. |
| sensitivity_expected_values | Compute Conditional Expected Values based on Outcome Model |
| sensitivity_expected_values.glm | Compute Conditional Expected Values based on Outcome Model |
| sensitivity_expected_values.lm | Compute Conditional Expected Values based on Outcome Model |
| sensitivity_expected_values.negbin | Compute Conditional Expected Values based on Outcome Model |