All:
I need to generate confidence intervals for differences in proportions using
data from a complex survey design. An example follows where I attempt to
estimate the difference in depression prevalence by sex.
# Data might look something like this:
Dfr<-data.frame(depression=sample(c("yes","n
Yihui,
This is quite impressive, thanks for helping me think about how to make tag
clouds in R.
Tony
-Original Message-
From: Yihui Xie [mailto:xieyi...@gmail.com]
Sent: Wednesday, June 10, 2009 3:15 AM
To: Brown, Tony Nicholas
Cc: r-help@r-project.org
Subject: Re: [R] graphically
Thank you so much Mark and Gregor. The basic information, suggestions,
and R code that you provided is most helpful.
Tony
-Original Message-
From: Gorjanc Gregor [mailto:gregor.gorj...@bfro.uni-lj.si]
Sent: Sunday, June 07, 2009 2:17 PM
To: Marc Schwartz; Brown, Tony Nicholas
Cc: rhelp
Dear all,
I recently saw a graph on television that displayed selected
words/phrases in a speech scaled in size according to their frequency.
So words/phrases that were often used appeared large and words that were
rarely used appeared small. The closest thing I can find on the web to
approxima
Thierry,
Thanks so much. Your solution works perfectly.
Tony
-Original Message-
From: ONKELINX, Thierry [mailto:[EMAIL PROTECTED]
Sent: Monday, September 15, 2008 2:56 AM
To: Brown, Tony Nicholas; r-help@r-project.org
Subject: RE: [R] randomly sample within clustered data?
Something
Dear useRs,
What is an efficient way to randomly sample from clustered data such
that I get equal representation from each cluster? For example, let's
say I want to randomly sample two cases from each cluster created by the
"id" variable in the following data frame:
> id<-c(rep("100", 4),re
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