Calculate Total Points and Probabilities for Nomogram
A nomogram, which can be carried out in 'rms' package, provides a
graphical explanation of a prediction process. However, it is not very easy
to draw straight lines, read points and probabilities accurately. Even, it
is hard for users to calculate total points and probabilities for all
subjects.
This package provides formula_rd() and formula_lp() functions to fit the
formula of total points with raw data and linear predictors respectively by
polynomial regression. Function points_cal() will help you calculate the
total points. formula_prob() and prob_cal() can be used to fit the formula of
probabilities and total points and calculate the probabilities.

A nomogram, which can be carried out in 'rms' package, provides a
graphical explanation of a prediction process. However, it is not very easy
to draw straight lines, read points and probabilities accurately. Even, it
is hard for users to calculate total points and probabilities for all
subjects.
This package provides formula_rd() and formula_lp() functions to fit the
formula of total points with raw data and linear predictors respectively by
polynomial regression. Function points_cal() will help you calculate the
total points. prob_cal() can be used to calculate the probabilities after
lrm(), cph() or psm() regression.

A nomogram, which can be carried out in 'rms' package, provides a
graphical explanation of a prediction process. However, it is not very easy
to draw straight lines, read points and probabilities accurately. Even, it
is hard for users to calculate total points and probabilities for all
subjects.
This package provides formula_rd() and formula_lp() functions to fit the
formula of total points with raw data and linear predictors respectively by
polynomial regression. Function points_cal() will help you calculate the
total points. prob_cal() can be used to calculate the probabilities after
lrm(), cph() or psm() regression.
For more complex condition, interaction or restricted cubic spine, TotalPoints.rms()
can be used.