Man pages for JanvandenBrand/jmmm
High Dimensional Joint Models
| average_hessians | Average the Hessians |
| binary.normal | Link function for the combination of a binary and continuous... |
| create_A_matrix | Create the helper 'A' matrix used to average the parameter... |
| get_auc | Calculate the Area under the Receiver Operating... |
| get_covariance | Calculate the covariance matrix for the MMM and return it and... |
| get_crossproducts | Get cross products of the gradients |
| get_likelihood_fail | Get Likelihood Fail |
| get_likelihood_nofail | Get Likelihood No Fail |
| get_likelihood_profiles_fail | Get likelihood profiles for failure |
| get_likelihood_profiles_nofail | Get likelihood profiles for non failures |
| get_mmm_derivatives | Determine the subject level derivatives. |
| get_mmm_start_values | Fit pairwise mixed models to get start values for the... |
| get_model_output | Create the full mixed model output |
| get_outcome_type | Return a data.frame with the outcome label and type |
| get_posteriors | Apply Bayes Rule to get posterior predictions |
| get_predictions_fail | Get Predictions for Failure |
| get_predictions_nofail | Get predictions for non failure |
| get_priors | Get priors |
| get_random_start | Create random start values |
| make_fixed_formula | Generate fixed formula for stacked data |
| make_pairs | Make pairs |
| make_random_formula | Generate random effects formula for stacked data |
| mmm_model | Fit a multivariate mixed model using the pairwise fitting... |
| mmm_predictions | Predictions from the multivariate mixed model using a... |
| normal | Link function for the combination of two continuous markers |
| plot_calibration | Plot the calibration for MMM |
| plot_predictions | Plot predictions from the multivariate mixed model |
| stack_data | Return a list with stacked data sets for each of the outcome... |
| stack_gradients | Stack gradients into a single data.frame |
| stack_parameters | Take the parameter estimates, add labels and stack them into... |
| test_compare_stacked_to_original_data | Test to compare stacked outcome data to original outcome data |
| test_input_datatypes | Test input data types and return model families and indicator... |
