reclass: Risk reclassification table

In ModelGood: Validation of risk prediction models

Description

Tabulate grouped risks predicted by two different methods, models, algorithms

Usage

reclass(list, newdata, cuts = seq(0, 100, 25), digits = 1)

Arguments

list	A list with two elements. Each element should either be a vector with probabilities, or an object for which predictStatusProb can extract predicted risk based on newdata.
newdata	Passed on to predictStatusProb
cuts	Risk quantiles to group risk
digits	Number of digits to show for the predicted risks

Details

All risks are multiplied by 100 before

Value

reclassification table

Author(s)

Thomas A. Gerds <[e-mail]>

See Also

predictStatusProb

Examples

set.seed(40)
N <- 40
X1 <- rnorm(N)
X2 <- rbinom(N,1,.4)
X3 <- rnorm(N)
expit <- function(x) exp(x)/(1+exp(x))
lp <- expit(X1 + X2 + X3)
Y <- factor(rbinom(N,1,lp))
dat <- data.frame(Y=Y,X1=X1,X2=X2,X3=X3)
lm1 <- glm(Y~X1,data=dat,family="binomial")
lm2 <- glm(Y~X1+X2,data=dat,family="binomial")

rc <- reclass(list("lrm.X1"=lm1,"lrm.X1.X2"=lm2),newdata=dat)
print(rc)
plot(rc)

rc2 <- reclass(list("lrm.X1"=lm1,"lrm.X1.X2"=lm2),newdata=dat,cuts=c(0,5,10,50,100))
print(rc2)
plot(rc2)

Example output

         lrm.X1.X2
lrm.X1    0-25% 25-50% 50-75% 75-100%
  0-25%       4      1      0       0
  25-50%      2     10      3       0
  50-75%      0      1     14       0
  75-100%     0      0      0       5
         lrm.X1.X2
lrm.X1    0-5% 5-10% 10-50% 50-100%
  0-5%       0     0      0       0
  5-10%      0     0      0       0
  10-50%     0     0     17       3
  50-100%    0     0      1      19

ModelGood documentation built on May 2, 2019, 3:02 a.m.