Package: predtools 0.0.3

Amin Adibi

predtools: Prediction Model Tools

Provides additional functions for evaluating predictive models, including plotting calibration curves and model-based Receiver Operating Characteristic (mROC) based on Sadatsafavi et al (2021) <arxiv:2003.00316>.

Authors:Mohsen Sadatsafavi [aut, cph], Amin Adibi [cre], Abdollah Safari [aut], Tae Yoon Lee [aut]

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predtools.pdf |predtools.html✨
predtools/json (API)
NEWS

# Install 'predtools' in R:

install.packages('predtools', repos = c('https://resplab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/resplab/predtools/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

dev_data - Model development data
gusto - Anonymized data from the gusto trial
val_data - Model validation data

On CRAN:

6.66 score 8 stars 71 scripts 373 downloads 11 exports 36 dependencies

Last updated 1 years agofrom:4d90f59c22. Checks:OK: 4 NOTE: 5. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 27 2024
R-4.5-win-x86_64	NOTE	Oct 27 2024
R-4.5-linux-x86_64	NOTE	Oct 27 2024
R-4.4-win-x86_64	NOTE	Oct 27 2024
R-4.4-mac-x86_64	NOTE	Oct 27 2024
R-4.4-mac-aarch64	NOTE	Oct 27 2024
R-4.3-win-x86_64	OK	Oct 27 2024
R-4.3-mac-x86_64	OK	Oct 27 2024
R-4.3-mac-aarch64	OK	Oct 27 2024

Exports:calc_mROC_stats calc_NB_moments calibration_plot evpi_val mAUC mROC mROC_analysis mROC_inference mu_max_trunc_bvn odds_adjust pred_summary_stat

Dependencies:cli colorspace dplyr fansi farver generics ggplot2 glue gtable isoband labeling lattice lifecycle magrittr MASS Matrix mgcv munsell mvtnorm nlme pillar pkgconfig plyr pROC R6 RColorBrewer RConics Rcpp rlang scales tibble tidyselect utf8 vctrs viridisLite withr

Calibration Plot

Rendered fromcalibPlot.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2022-08-08
Started: 2021-09-25

Intercept Adjustment

Rendered frominterceptAdj.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2022-07-08
Started: 2021-09-24

Model-based ROC

Rendered frommROC.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2021-09-24
Started: 2021-09-13

Unit Normal Loss Integral in Two Dimensions

Rendered fromUNLI2D.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2022-10-19
Started: 2022-10-19

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Calculates the absolute surface between the empirical and expected ROCs	calc_mROC_stats
Calculates the first two moments of the bivariate distribution of NB_model and NB_all	calc_NB_moments
Title Create calibration plot based on observed and predicted outcomes.	calibration_plot
model development data	dev_data
EVPI (Expected Value of Perfect Information) for validation Takes a vector of mean and a 2X2 covariance matrix	evpi_val
Anonymized data from the gusto trial	gusto
Takes in a mROC object and calculates the area under the curve	mAUC
Calculates mROC from the vector of predicted risks Takes in a vector of probabilities and returns mROC values (True positives, False Positives in an object of class mROC)	mROC
Main eROC analysis that plots ROC and eROC	mROC_analysis
Statistical inference for comparing empirical and expected ROCs. If CI=TRUE then also returns pointwise CIs	mROC_inference
Calculates the expected value of the maximum of two random variables with zero-truncated bivariate normal distribution Takes a vector of mean and a 2X2 covariance matrix	mu_max_trunc_bvn
Title Update a prediction model for a binary outcome by multiplying a fixed odd-ratio to the predicted odds.	odds_adjust
Title Estimate mean and variance of prediction based on model calibration output.	pred_summary_stat
model validation data	val_data