validate | R Documentation |
The validate
function when used on an object created by one of the
rms
series does resampling validation of a
regression model, with or without backward step-down variable
deletion.
The print
method will call the latex
or html
method
if options(prType=)
is set to "latex"
or "html"
.
For "latex"
printing through print()
, the LaTeX table
environment is turned off. When using html with Quarto or RMarkdown,
results='asis'
need not be written in the chunk header.
# fit <- fitting.function(formula=response ~ terms, x=TRUE, y=TRUE)
validate(fit, method="boot", B=40,
bw=FALSE, rule="aic", type="residual", sls=0.05, aics=0,
force=NULL, estimates=TRUE, pr=FALSE, ...)
## S3 method for class 'validate'
print(x, digits=4, B=Inf, ...)
## S3 method for class 'validate'
latex(object, digits=4, B=Inf, file='', append=FALSE,
title=first.word(deparse(substitute(x))),
caption=NULL, table.env=FALSE,
size='normalsize', extracolsize=size, ...)
## S3 method for class 'validate'
html(object, digits=4, B=Inf, caption=NULL, ...)
fit |
a fit derived by e.g. |
method |
may be |
B |
number of repetitions. For |
bw |
|
rule |
Applies if |
type |
|
sls |
significance level for a factor to be kept in a model, or for judging the
residual |
aics |
cutoff on AIC when |
force |
see |
estimates |
see |
pr |
|
... |
parameters for each specific validate function, and parameters to
pass to For For |
x , object |
an object produced by one of the |
digits |
number of decimal places to print |
file |
file to write LaTeX output. Default is standard output. |
append |
set to |
title , caption , table.env , extracolsize |
see
|
size |
size of LaTeX output. Default is |
It provides bias-corrected indexes that are specific to each type
of model. For validate.cph
and validate.psm
, see validate.lrm
,
which is similar.
For validate.cph
and validate.psm
, there is
an extra argument dxy
, which if TRUE
causes the dxy.cens
function to be invoked to compute the Somers' D_{xy}
rank correlation
to be computed at each resample. The values corresponding to the row
D_{xy}
are equal to 2 * (C - 0.5)
where C is the
C-index or concordance probability.
For validate.cph
with dxy=TRUE
,
you must specify an argument u
if the model is stratified, since
survival curves can then cross and X\beta
is not 1-1 with
predicted survival.
There is also validate
method for
tree
, which only does cross-validation and which has a different
list of arguments.
a matrix with rows corresponding to the statistical indexes and columns for columns for the original index, resample estimates, indexes applied to the whole or omitted sample using the model derived from the resample, average optimism, corrected index, and number of successful re-samples.
prints a summary, and optionally statistics for each re-fit
Frank Harrell
Department of Biostatistics, Vanderbilt University
fh@fharrell.com
validate.ols
, validate.cph
,
validate.lrm
, validate.rpart
,
predab.resample
, fastbw
, rms
,
rms.trans
, calibrate
,
dxy.cens
, concordancefit
# See examples for validate.cph, validate.lrm, validate.ols
# Example of validating a parametric survival model:
require(survival)
n <- 1000
set.seed(731)
age <- 50 + 12*rnorm(n)
label(age) <- "Age"
sex <- factor(sample(c('Male','Female'), n, TRUE))
cens <- 15*runif(n)
h <- .02*exp(.04*(age-50)+.8*(sex=='Female'))
dt <- -log(runif(n))/h
e <- ifelse(dt <= cens,1,0)
dt <- pmin(dt, cens)
units(dt) <- "Year"
S <- Surv(dt,e)
f <- psm(S ~ age*sex, x=TRUE, y=TRUE) # Weibull model
# Validate full model fit
validate(f, B=10) # usually B=150
# Validate stepwise model with typical (not so good) stopping rule
# bw=TRUE does not preserve hierarchy of terms at present
validate(f, B=10, bw=TRUE, rule="p", sls=.1, type="individual")
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