Thank you very much for the help!
Now, I have an additional question regarding transcending from Design to
rms: Before, it was possible to plot interaction, and get lines with
plot(ols2, gender=NA, marital.status=NA, xlab='gender',
ylab='anxiety', conf.int=FALSE)
Now, I am lost how to do that. If model is:
ols2 <- ols(anxiety ~ marital.status * gender)
Then, I need:
p2 <- Predict(ols2, marital.status=., gender=.)
And plot(p2) does not give me lines, but points with conf.int. Also,
axes are transposed as to what old plot(ols2) would give.
In addition, if I try old function (plot(ols2), above), error message
returns:
Error in predictDesign(fit, adj, type = "x", non.slopes = non.slopes)
could not find function "Varcov"
Best,
PM
Frank E Harrell Jr wrote:
Petar Milin wrote:
I would like to have a line on this plot, instead of two points:
x1 = rnorm(100, 10, 2.5)
x2 = rnorm(100, 26, 3.2)
x1 = as.data.frame(x1)
x2 = as.data.frame(x2)
colnames(x1) = 'anxiety'
colnames(x2) = 'anxiety'
x1$gender = 'male'
x2$gender = 'female'
dat = rbind(x1, x2)
require(Design)
attach(dat)
d=datadist(gender)
options(datadist="d")
ols1 <- ols(anxiety ~ gender, data=dat, x=T, y=T)
plot(ols1, gender=NA, xlab="gender", ylab="anxiety",
ylim=c(5,30), conf.int=FALSE)
detach(dat)
Your code has many problems and inefficiencies in it. Here are some
suggested fixes and the commands needed using the new rms package:
require(rms)
n <- 100
anxiety <- c(rnorm(n, 10, 2.5), rnorm(n, 26, 3.2))
gender <- c(rep('male', n), rep('female',n))
d <- datadist(gender); options(datadist='d')
f <- ols(anxiety ~ gender)
p <- Predict(f, gender=.)
# For this case could also do p <- Predict(f); plot(p) would give a
# vertical dot chart
p # print estimates
plot(p) # horizontal dot chart; preferred for categorical predictors
# To take control using lines:
with(p, plot(1:2, yhat, type='l', xlab='gender numeric'))
Frank
Thanks!
PM
Frank E Harrell Jr wrote:
Petar Milin wrote:
Hello ALL!
I have a problem to plot factor (lets say gender) as a line, or at
least both line and point, from ols model:
ols1 <- ols(Y ~ gender, data=dat, x=T, y=T)
plot(ols1, gender=NA, xlab="gender", ylab="Y",
ylim=c(5,30), conf.int=FALSE)
If I convert gender into discrete numeric predictor, and use
forceLines=TRUE, plot is not nice and true, since it shows values
between 1 and 2.
Thanks!
PM
Petar,
forceLines seems to be doing what it was intended to do. I'm not
clear on why you need a line, though. If you provide self-contained
code and data that replicate your problem I may be able to help more,
or you can try a new package I'm about to announce.
Frank
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