R help - May 2011 - can not use plot.Predict {rms} reproduce figure 7.8 from Regression Modeling Strategies (http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf)

Dear R-users,

I am using R 2.13.0 and rms 3.3-0 , but can not reproduce figure 7.8 of the
handouts *Regression Modeling Strategies* (
http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf) by the
following code. Could any one help me figure out how to solve this?


setwd('C:/Rharrell')
require(rms)
load('data/counties.sav')

older <- counties$age6574 + counties$age75
label(older) <- '% age >= 65, 1990'
pdensity <- logb(counties$pop.density+1, 10)
label(pdensity) <- 'log 10 of 1992 pop per 1990 miles^2'
counties <- cbind(counties, older, pdensity)  # add 2 vars. not in data
frame
dd <- datadist(counties)
options(datadist='dd')

f <- ols(democrat ~ rcs(pdensity,4) + rcs(pop.change,3) +
         rcs(older,3) + crime + rcs(college,5) + rcs(income,4) +
         rcs(college,5) %ia% rcs(income,4) +
         rcs(farm,3) + rcs(white,5) + rcs(turnout,3), data=counties)

incomes <- seq(22900, 32800, length=4)
show.pts <- function(college.pts, income.pt)
  {
    s <- abs(income - income.pt) < 1650
                                        # Compute 10th smallest and 10th
largest % college
                                        # educated in counties with median
family income within
                                        # $1650 of the target income
    x <- college[s]
    x <- sort(x[!is.na(x)])
    n <- length(x)
    low <- x[10]; high <- x[n-9]
    college.pts >= low & college.pts <= high
  }
windows()
plot(Predict(f, college, income=incomes, conf.int=FALSE),
     xlim=c(0,35), ylim=c(30,55), lty=1, lwd=c(.25,1.5,3.5,6),
col=c(1,1,2,2), perim=show.pts)




Thanks

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Also I can not reproduce figure 7.11 by

f <- Newlabels(f, list(turnout='voter turnout (%)'))
windows()
nomogram(f, interact=list(income=incomes), turnout=seq(30,100,by=10),
         lplabel='estimated % voting Democratic', cex.var=.8,
cex.axis=.75)



On Tue, May 17, 2011 at 4:04 PM, John Smith <zmring@gmail.com> wrote:
> Dear R-users,
>
> I am using R 2.13.0 and rms 3.3-0 , but can not reproduce figure 7.8 of the
> handouts *Regression Modeling Strategies* (
> http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf) by the
> following code. Could any one help me figure out how to solve this?
>
>
> setwd('C:/Rharrell')
> require(rms)
> load('data/counties.sav')
>
> older <- counties$age6574 + counties$age75
> label(older) <- '% age >= 65, 1990'
> pdensity <- logb(counties$pop.density+1, 10)
> label(pdensity) <- 'log 10 of 1992 pop per 1990 miles^2'
> counties <- cbind(counties, older, pdensity)  # add 2 vars. not in data
> frame
> dd <- datadist(counties)
> options(datadist='dd')
>
> f <- ols(democrat ~ rcs(pdensity,4) + rcs(pop.change,3) +
>          rcs(older,3) + crime + rcs(college,5) + rcs(income,4) +
>          rcs(college,5) %ia% rcs(income,4) +
>          rcs(farm,3) + rcs(white,5) + rcs(turnout,3), data=counties)
>
> incomes <- seq(22900, 32800, length=4)
> show.pts <- function(college.pts, income.pt)
>   {
>     s <- abs(income - income.pt) < 1650
>                                         # Compute 10th smallest and 10th
> largest % college
>                                         # educated in counties with median
> family income within
>                                         # $1650 of the target income
>     x <- college[s]
>     x <- sort(x[!is.na(x)])
>     n <- length(x)
>     low <- x[10]; high <- x[n-9]
>     college.pts >= low & college.pts <= high
>   }
> windows()
> plot(Predict(f, college, income=incomes, conf.int=FALSE),
>      xlim=c(0,35), ylim=c(30,55), lty=1, lwd=c(.25,1.5,3.5,6),
> col=c(1,1,2,2), perim=show.pts)
>
>
>
>
> Thanks
>
>
>
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With most current version of R and RMS, the 4 curves are drew in
4 separate panels. Can anyone show me how can I get the figure exactly like
the figure 7.8 in  *Regression Modeling Strategies* (
http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf)

Thanks




On Tue, May 17, 2011 at 4:04 PM, John Smith <zmring@gmail.com> wrote:
> Dear R-users,
>
> I am using R 2.13.0 and rms 3.3-0 , but can not reproduce figure 7.8 of
> the handouts *Regression Modeling Strategies* (
> http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf) by the
> following code. Could any one help me figure out how to solve this?
>
>
> setwd('C:/Rharrell')
> require(rms)
> load('data/counties.sav')
>
> older <- counties$age6574 + counties$age75
> label(older) <- '% age >= 65, 1990'
> pdensity <- logb(counties$pop.density+1, 10)
> label(pdensity) <- 'log 10 of 1992 pop per 1990 miles^2'
> counties <- cbind(counties, older, pdensity)  # add 2 vars. not in data
> frame
> dd <- datadist(counties)
> options(datadist='dd')
>
> f <- ols(democrat ~ rcs(pdensity,4) + rcs(pop.change,3) +
>          rcs(older,3) + crime + rcs(college,5) + rcs(income,4) +
>          rcs(college,5) %ia% rcs(income,4) +
>          rcs(farm,3) + rcs(white,5) + rcs(turnout,3), data=counties)
>
> incomes <- seq(22900, 32800, length=4)
> show.pts <- function(college.pts, income.pt)
>   {
>     s <- abs(income - income.pt) < 1650
>                                         # Compute 10th smallest and 10th
> largest % college
>                                         # educated in counties with median
> family income within
>                                         # $1650 of the target income
>     x <- college[s]
>     x <- sort(x[!is.na(x)])
>     n <- length(x)
>     low <- x[10]; high <- x[n-9]
>     college.pts >= low & college.pts <= high
>   }
> windows()
> plot(Predict(f, college, income=incomes, conf.int=FALSE),
>      xlim=c(0,35), ylim=c(30,55), lty=1, lwd=c(.25,1.5,3.5,6),
> col=c(1,1,2,2), perim=show.pts)
>
>
>
>
> Thanks
>
>
>
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