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This R-package provides functions to calculate the unadjusted, the adjusted and the marginal Laupacis NNT with the corresponding 95% confidence intervals. Available regression models include ANOVA, regression, and Cox models. In addition, the package provides a function to calculate the Kaplan Meier NNT, and Kraemer & Kupfer's NNT.

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nntcalc: The Number Needed to Treat (NNT) calculator

Valentin Vancak

The nntcalc R-package provides functions to calculate the unadjusted, the conditional (adjusted), and the harmonic mean (marginal) Laupacis NNT with the corresponding 95% confidence intervals. Available regression models include ANOVA, linear regression and logistic regression, and Cox models. In addition, the package provides a function to calculate the estimators of the Kraemer & Kupfer's NNT.

For the installation of nntcalc you need to load first the devtools package by library(devtools), and then type

install_github("https://github.com/vancak/NNTcalculator")

Tha package is called nntcalc. To load it after installation type

library(nntcalc)

For further details and examples please see package manual.

NOTE: The source code for the simulations presented in the manuscript "The Number Needed to Treat Adjusted for Explanatory Variables in Regression and Survival Analysis: Theory and Application" is available here.

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This R-package provides functions to calculate the unadjusted, the adjusted and the marginal Laupacis NNT with the corresponding 95% confidence intervals. Available regression models include ANOVA, regression, and Cox models. In addition, the package provides a function to calculate the Kaplan Meier NNT, and Kraemer & Kupfer's NNT.

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