apply_acd |
Function to apply Approximate Cumulative Distribution (ACD) |
apply_shift_scale |
Shift and scale vector x |
art |
Artificial dataset with continuous response |
assign_df |
Helper to assign degrees of freedom |
calculate_df |
Helper to calculates the final degrees of freedom for the selected model |
calculate_f_test |
Function to compute F-statistic and p-value from deviances |
calculate_lr_test |
Function to calculate p-values for likelihood-ratio test |
calculate_model_metrics |
Function to compute model metrics to be used within 'mfp2' |
calculate_number_fp_powers |
Calculates the total number of fractional polynomial powers in adjustment variables. |
calculate_standard_error |
Helper function to compute standard error of a partial predictor |
center_matrix |
Simple function to center data |
coef.mfp2 |
Extract coefficients from object of class 'mfp2' |
convert_powers_list_to_matrix |
Helper to convert a nested list with same or different length into a matrix |
create_dummy_variables |
Simple function to create dummy variables for ordinal and nominal variables |
create_fp_terms |
Helper to create overview table of fp terms |
deviance_gaussian |
Deviance computations as used in mfp in stata |
ensure_length |
Helper function to ensure vectors have a specified length |
find_best_fp1_for_acd |
Function to fit univariable FP1 models for acd transformation |
find_best_fpm_step |
Function to find the best FP functions of given degree for a single variable |
find_best_fp_cycle |
Helper to run cycles of the mfp algorithm |
find_best_fp_step |
Function to estimate the best FP functions for a single variable |
find_scale_factor |
Function that calculates an integer used to scale predictor |
find_shift_factor |
Function that calculates a value used to shift predictor |
fit_acd |
Function to estimate approximate cumulative distribution (ACD) |
fit_cox |
Function that fits Cox proportional hazards models |
fit_glm |
Function that fits generalized linear models |
fit_linear_step |
Function to fit linear model for variable of interest |
fit_mfp |
Function for fitting a model using the MFP or MFPA algorithm |
fit_model |
Function that fits models supported by 'mfp2' |
fit_null_step |
Function to fit null model excluding variable of interest |
fp |
Helper to assign attributes to a variable undergoing FP-transformation |
fp2 |
Helper to assign attributes to a variable undergoing FP-transformation |
fracplot |
Plot response functions from a fitted 'mfp2' object |
gbsg |
Breast cancer dataset used in the Royston and Sauerbrei (2008) book. |
generate_combinations_with_replacement |
Helper function to generate combinations with replacement |
generate_powers_acd |
Function that generates a matrix of FP powers for any degree |
generate_powers_fp |
Function that generates a matrix of FP powers for any degree |
generate_transformations_acd |
Function to generate all requested FP transformations for a single variable |
generate_transformations_fp |
Function to generate all requested FP transformations for a single variable |
get_selected_variable_names |
Helper function to extract selected variables from fitted 'mfp2' object |
mfp2 |
Multivariable Fractional Polynomial Models with Extensions |
mfp2.default |
Multivariable Fractional Polynomial Models with Extensions |
mfp2.formula |
Multivariable Fractional Polynomial Models with Extensions |
name_transformed_variables |
Helper function to name transformed variables |
order_variables |
Helper to order variables for mfp2 algorithm |
order_variables_by_significance |
Helper to order variables for mfp2 algorithm |
pima |
Pima Indians dataset used in the Royston and Sauerbrei (2008) book. |
plot_mfp |
Plot response functions from a fitted 'mfp2' object |
predict.mfp2 |
Predict Method for 'mfp2' Fits |
prepare_newdata_for_predict |
Helper function to prepare newdata for predict function |
print.mfp2 |
Print method for objects of class 'mfp2' |
print_mfp_ic_step |
Function for verbose printing of function selection procedure (FSP) |
print_mfp_pvalue_step |
Function for verbose printing of function selection procedure (FSP) |
print_mfp_step |
Function for verbose printing of function selection procedure (FSP) |
prostate |
Prostate cancer dataset used in the Royston and Sauerbrei (2008) book. |
reset_acd |
Helper to reset acd transformation for variables with few values |
select_ic |
Function selection procedure based on information criteria |
select_ic_acd |
Function selection procedure based on information criteria |
select_linear |
Helper to select between null and linear term for a single variable |
select_ra2 |
Function selection procedure based on closed testing procedure |
select_ra2_acd |
Function selection procedure for ACD based on closed testing procedure |
summary.mfp2 |
Summarizing 'mfp2' model fits |
transform_data_step |
Function to extract and transform adjustment variables |
transform_matrix |
Function to transform each column of matrix using final FP powers or acd |
transform_vector_acd |
Functions to transform a variable using fractional polynomial powers or acd |
transform_vector_fp |
Functions to transform a variable using fractional polynomial powers or acd |
transform_vector_power |
Simple function to transform vector by a single power |