R: Multivariable Fractional Polynomial Models with Extensions

# Multivariable Fractional Polynomial Models with Extensions

## Documentation for package ‘mfp2’ version 1.0.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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
backscale_matrix | Backscale Columns of a Matrix (Internal)
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'
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