> On Jan 3, 2018, at 11:57 AM, Andras Farkas via R-help <r-help@r-project.org>
> wrote:
>
> Dear All,
> using the example from the help of summary.rms
>
> library(rms)
> n <- 1000 # define sample size
> set.seed(17) # so can reproduce the results
> age <- rnorm(n, 50, 10)
> blood.pressure <- rnorm(n, 120, 15)
> cholesterol <- rnorm(n, 200, 25)
> sex <- factor(sample(c('female','male'), n,TRUE))
> label(age) <- 'Age' # label is in Hmisc
> label(cholesterol) <- 'Total Cholesterol'
> label(blood.pressure) <- 'Systolic Blood Pressure'
> label(sex) <- 'Sex'
> units(cholesterol) <- 'mg/dl' # uses units.default in Hmisc
> units(blood.pressure) <- 'mmHg'
> # Specify population model for log odds that Y=1
> L <- .4*(sex=='male') + .045*(age-50) +
> (log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))
> # Simulate binary y to have Prob(y=1) = 1/[1+exp(-L)]
> y <- ifelse(runif(n) < plogis(L), 1, 0)
> ddist <- datadist(age, blood.pressure, cholesterol, sex)
> options(datadist='ddist')
> fit <- lrm(y ~ blood.pressure + sex * (age + rcs(cholesterol,4)))
> s <- summary(fit)
> plot(s)
> as you will see the plot will by default include the low and high values from
> the summary printed on the plot to the right of the variable name... Any
> thoughts on how printing these low and high values can be suppressed, ie:
> prevent them from being printed?
>
Luke, ... Look at the code!
The values are suppressed if the "Diff." has NA's so ...
s[ , "Diff."] <- NA
plot(s)
--
David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law
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