Question 2: Try saving the data as an SPSS portable file. I never had
trouble reading these in R.
Finn Sandø wrote:
> When I try to import an spss sav file with read.spss() I am getting the
> following error
> 'Error in read.spss("X:\\.sav") : error reading system-file header'
> and the imp
Like the error message tells you, cor does not have an argument "na.rm".
use="complete" already does what you want, namely casewise deletion of
missing values.
However, this will not work with vectors of unequal length (how is R to
determine which observations in x correspond to those in y?). W
http://cran.r-project.org/bin/windows/base/rw-FAQ.html#What_0027s-the-best-way-to-upgrade_003f
[EMAIL PROTECTED] wrote:
> Hello everyone.
>
> Currently I am running R 2.2.1 (windows), and I will like to update to
> 2.3. I wanted to ask if it is possible to update without having to removed
> 2.2.
Hello,
and sorry if this is already explained somewhere. I couldn't find anything.
R (2.3.1, Windows) seems to perform some kind of lazy evaluation when
evaluating defaults in function calls that, at least for me, leads to
unexpected results. Consider the following, seemingly equivalent functio
Hello,
I'm sorry to resurrect this thread that I started almost two months ago.
I've been pretty busy since I posted my question and the issue is not
that high on my priority list. Thanks to all those who replied, and I
hope I can tickle your interest again.
As a reminder, my question was how
Vielen Dank, Spencer.
I could not find a published example where both the original data and
conditional posterior variances were available. Instead, I toyed around
a little with artificial data, and the (pretty pathetic) result below is
the closest I came to "Monte Carlo-ing". I'm afraid I lack
Hello,
I am looking for a way to obtain standard errors for emprirical Bayes estimates
of a model fitted with lmer (like the ones plotted on page 14 of the document
available at
http://www.eric.ed.gov/ERICDocs/data/ericdocs2/content_storage_01/000b/80/2b/b3/94.pdf).
Harold Doran mentioned
Hello,
this is not really an R-related question, but since the posting guide does not
forbid asking non-R questions (even encourages it to some degree), I though I'd
give it a try.
I am currently doing some secondary analyses of the PISA (http://pisa.oecd.org)
student data. I would like to treat
Hello everyone,
I use latex() (Hmisc) for report generation and thus have been affected by
the problem with rounding decimals described, for example, in this post:
http://thread.gmane.org/gmane.comp.lang.r.general/73287/focus=73287
In short, numbers often are printed with 15 or so decimals even
I am trying to read a number of XML files using xmlTreeParse(). Unfortunately,
some of them are malformed in a way that makes R crash. The problem is that
closing tags are sometimes repeated like this:
value1value2some garbagevalue3
I want to preprocess the contents of the XML file using gsub() b
Duncan Temple Lang wald.ucdavis.edu> writes:
> If xmlTreeParse() is actually causing R to exit (i.e. what some people
> refer to as crashing), as Jeff (Horner) said, we would like to be able
> to stop this. We will need the actual text/file passed to
> xmlTreeParse(), version information of operat
Hello,
Working on a little primer to ease the transition from SPSS to R, I have
encountered two problems with write.foreign.
One is cosmetic (but still annoying): the text data files will contain
"NA" for missing values. Each time SPSS encounters an NA, it will print
a warning. This could be e
fix(data)
will invoke edit(data) and store changes you make in data without
displaying anything.
stat stat schrieb:
> Dear all R users,
>
> I have a query on "Edit" function. Suppose I have a data frame named
> "data". I can use EDIT function to see the materials contained in data, by
>
I am not sure I understand what you want to do, but maybe some of this
will be helpful. I first generate some data that should resemble yours:
dat<-expand.grid(Region=1:3, Species=1:4, Sex=c("M","F"))
dat<-do.call("rbind",lapply(1:10,function(x) dat))
dat$Bodysize<-rnorm(nrow(dat),10,2)
Now what
Hello,
suppose I have a multivariate multiple regression model such as the
following:
> DF<-data.frame(x1=rep(c(0,1),each=50),x2=rep(c(0,1),50))
> tmp<-rnorm(100)
> DF$y1<-tmp+DF$x1*.5+DF$x2*.3+rnorm(100,0,.5)
> DF$y2<-tmp+DF$x1*.5+DF$x2*.7+rnorm(100,0,.5)
> x.mlm<-lm(cbind(y1,y2)~x1+x2,dat
Hello and thank you for your answers, Andrew and Berwin. If I'm not
mistaken, the mixed-model version of Berwin's approach would be:
#My stuff:
DF<-data.frame(x1=rep(c(0,1),each=50),x2=rep(c(0,1),50))
tmp<-rnorm(100)
DF$y1<-tmp+DF$x1*.5+DF$x2*.3+rnorm(100,0,.5)
DF$y2<-tmp+DF$x1*.5+DF$x2*.7+rnorm(
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