1. under unix prompt %, type "add
st370_info"
2. type "ESS R" under unix prompt %;
you will see an emacs window; you may want to hit several "return" key
until you get an R prompt >.
3. Include library "survival",
"Design" and
"KMsurv" by typing "library(survival)", "library( Design)", "library(
KMsurv)", each of which is under R prompt ">"; then you
can use most of the R functions for survival analysis.
4. The following is a list of functions available in the Design library:
ols
Ordinary least squares linear model
lrm
Binary and ordinal logistic regression model
psm
Accelerated failure time parametric survival model
cph
Cox proportional hazards regression
bj
Buckley-James censored least squares linear model
specs
Detailed specifications of fit
robcov
Robust covariance matrix estimates
bootcov
Bootstrap covariance matrix estimates
summary
Summary of effects of predictors
plot.summary
Plot continuously shaded confidence
bars for results of summary
anova
Wald tests of most meaningful hypotheses
contrast
General contrasts, C.L.,
tests
plot.anova Depict results
of anova graphically
plot
Plot effects of predictors
gendata
Generate data frame with predictor
combinations (optionally interactively)
predict
Obtain predicted values or design matrix
fastbw
Fast backward step-down variable
selection
residuals Residuals,
influence statistics from fit
which.influence
Which observations are overly influential
sensuc
Sensitivity of one binary predictor in
lrm and cph models to an unmeasured
binary confounder
latex
LaTeX representation of fitted
model or anova() table
Function S
function analytic representation
of a fitted regression model (X*Beta)
Hazard
S function analytic representation
of a fitted hazard function (for psm)
Survival S
function analytic representation of
fitted survival function (for psm,cph)
Quantile S
function analytic representation of
fitted function for quantiles of
survival time (for psm, cph)
nomogram Draws
a nomogram for the fitted model
survest
Estimate survival probabilities (for psm, cph)
survplot Plot
survival curves (psm, cph)
validate
Validate indexes of model fit using resampling
calibrate Estimate
calibration curve for model using resampling
vif
Variance inflation factors for a fit
naresid
Bring elements corresponding to missing
data back into predictions and residuals
naprint
Print summary of missing values
pentrace Find
optimum penality for penalized MLE
effective.df
Print effective d.f. for each type of
variable in model, for penalized fit or pentrace result
rm.impute Impute
repeated measures data with
non-random dropout (experimental function, not working
correctly)