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Hi all, I'm currently working with a dataset that has quite a few missing values and after some investigation I figured that multiple imputation is probably the best solution to handle the missing data in my case. I found several references to functions in S-Plus that perform multiple imputation (NORM, CAT, MIX, PAN). Does R have corresponding functions? I searched the archives but was not

Dear all; I am trying to use HMISC imputation function to perform multiple imputations on my data and I keep on getting errors for the code given in the help files. When using "aregImpute" the error is; >f <- aregImpute(~y + x1 + x2 + x3, n.impute=100) Loading required package: acepack Iteration:1 Error in .Fortran("wclosepw", as.double(w), as.double(x),

Hi, I have the following problem (library Hmisc loaded, iris data loaded, R Version 1.7.0 (2003-04-16), packages updated, running on a linux Debian i386): > summary(Species~Sepal.Length,method="reverse")->a > a Descriptive Statistics by Species +------------+-----------------+-----------------+-----------------+ | |setosa |versicolor |virginica

Dear R-helpers, When I try > anova(txtE2.lme, txtE2.lme1) Model df AIC BIC logLik Test L.Ratio p-value txtE2.lme 1 10 8590 8638 -4285 txtE2.lme1 2 7 8591 8624 -4288 1 vs 2 6.79 0.0789 > latex(anova(txtE2.lme, txtE2.lme1)) Error: object "n.group" not found I don't even see n.group as one of the arguments of latex() I checked to see >

I'm looking for an R method to produce latex versions of tables for table/array objects of 3 or more dimensions, which, of necessity is flattened to a 2D display, for example with ftable(), or vcd::structable, as shown below. I'd be happy to settle for a flexible solution for the 3D case. > UCB <- aperm(UCBAdmissions, c(2, 1, 3)) > ftable(UCB) Dept A B

Forgive my ignorance, but how I can take a look at the code for the latex function in the Hmisc library? I tried just typing "latex" but all I got was this: > latex function (object, title = first.word(deparse(substitute(object))), ...) { if (!length(oldClass(object))) oldClass(object) <- data.class(object) UseMethod("latex") } What should I do?

I'm interested in finding a package in R to do multiple imputations, similar to MICE in S-Plus. Does one exist? Please email directly to me. Thanks. Linda Andrews Social & Scientific Systems (301) 628-3234 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

I have always avoided missing data by keeping my distance from the real world. But I have a student who is doing a study of real patients. We're trying to test regression models using multiple imputation. We did the following (roughly): f <- aregImpute(~ [list of 32 variables, separated by + signs], n.impute=20, defaultLinear=T, data=t1) # I read that 20 is better than the default of

On Mon, 16 Jun 2003 09:56:07 +0200 Patrick Hausmann <p.hausmann at mr-regionalberatung.de> wrote: > Dear Frank, > > I can reproduce the problem from Philippe Glaziou (see attachment). > Maybe this can help. > Best, > Patrick > > Am Wollelager 11 > 27749 Delmenhorst > Tel. 04221 96373-0 > Fax 04221 96373-29 > > http://www.mr-regionalberatung.de >

I am a new user of R for Windows, enthusiast about the many functions of the Design and Hmisc libraries. I combined the results of a Cox regression model after multiple imputation (of missing values in some covariates). Now I got my vector of coefficients (and of standard errors). My question is: How could I use directly that vector to run programs such as 'nomogram', 'calibrate',

Hi Folks, I'm currently looking at missing data/imputation methods (including multiple imputation). S-Plus has a "missing data library". What similar resources are available within R? Or does one roll one's own? Best wishes to all, Ted. -------------------------------------------------------------------- E-Mail: (Ted Harding) <Ted.Harding at nessie.mcc.ac.uk>

Hi, This is (presumably?) a bug in R 1.7.0 under Windows. I have not tested it on other systems. Attachment of packages is case sensitive but not library(), resulting in multiple loadings of the same package if the library name is spelled differently. The following example loads the `tools' package, once as `tools' and once as `Tools'. This behavior is the same with all packages and

>From Internet I downloaded the file Hmisc.zip and used it for R package updation. and R gave the message 'Hmisc' successfull unpacked. But when I use the functions like aregImpute the package is displaying coundn't find the function Where as in help.search it is giving that use of the function >

The Design library has been fully ported to R except for Cox proportional hazards regression modeling (using Therneau's survival package) which will be available in about two weeks. It will take much longer to make all the example code executable, is it currently contains many examples for which data are not provided. Thanks to Xiao Gang Fan <xiao.gang.fan1 at libertysurf.fr> who

The Design library has been fully ported to R except for Cox proportional hazards regression modeling (using Therneau's survival package) which will be available in about two weeks. It will take much longer to make all the example code executable, is it currently contains many examples for which data are not provided. Thanks to Xiao Gang Fan <xiao.gang.fan1 at libertysurf.fr> who

In a .First.lib I want to issue two require()s to insure that two other packages are loaded. But I want the package being loaded by .First.lib using library.dynam("mypackage",pkb,lib) to be higher in the search order than the two required packages, because I want to have a couple of functions from the two required packages overridden. What is the best way to do that? Thanks in advance

Hi Folks, I've got a question regarding the 'quantreg' package maintained by Roger Koenker: I tried to produce LaTeX tables using the longtable and dcolumn options as decribed in the manual, but the function latex() doesn't seem to react on _any_ other options than 'digits' and 'transpose'. To reproduce these results the following minimal example may be used:

Hello: I'm working with a 2-dimensional table that looks sort of like test below. I'm trying to produce latex code that will add dimension names for both the rows and the columns. In using the following code, latex chokes when I include collabel='Vote' but it's fine without it. The code below prouces the latex code further below. I'm confused by this, because it looks

Here is a programming question. The code I am using is quite slow and I was wondering if there is a way to get rid of the for loop. I am dealing with "interaction" in 2x2 table, and am using Edwards's G_I (Likelihood, p. 194). I label the cells in the table as follows stim response "y" "n" total -------------------------------- y hit miss nsignal

Hello R-user I want to compute a multiple regression but I would to include a check for collinearity of the variables. Therefore I would like to use a ridge regression. I tried lm.ridge() but I don't know yet how to get p-values (single Pr() and p of the whole model) out of this model. Can anybody tell me how to get a similar output like the summary(lm(...)) output? Or if there is