similar to: Optional data argument for a function

I was not sure who I should contact about this, so I am posting this here. There are a few broken links on the R website. 1) http://www.r-project.org/search.html -> link to the Nabble R Forum. I belive the correct/new URL should be: http://r.789695.n4.nabble.com/ 2) http://www.r-project.org/other-docs.html -> link to "Auswertung ?kologischer Daten". Not sure if there is a new

Dear All, Suppose I want to write a method for the generic function confint(): > args(confint) function (object, parm, level = 0.95, ...) So, it looks like the second and third argument have been predefined in the generic function. Suppose one or several of the predefined arguments don't apply or fit (in some sense) with the design of the rest of the package. What should one do? I see

Dear All, I have been checking the metafor package against R-devel. R CMD check --as-cran metafor yields one note: FOSS licence with BuildVignettes: false Yes, I have 'BuildVignettes: FALSE' in my DESCRIPTION file. I see at http://developer.r-project.org/blosxom.cgi/R-devel/NEWS: Tue, 25 Jun 2013 CHANGES IN R-devel UTILITIES 'R CMD check --as-cran' warns about a false

Hi all, Just noticed that the error that arises when calling t.test() with factors could be a bit clearer: > t.test(factor(c(3,1,2,4,3,5,4,5)), factor(c(2,1,2,3,4,5))) Error in var(x) : Calling var(x) on a factor x is defunct. Use something like 'all(duplicated(x)[-1L])' to test for a constant vector. In addition: Warning message: In mean.default(x) : argument is not numeric or

Hi All, I am compiling R-devel on Linux (Ubuntu 16.04.2) and that works just fine, but I am missing some of the expected features, as shown here: https://cran.r-project.org/doc/manuals/r-devel/R-admin.html#Linux In particular, after configure (using all defaults), I see: R is now configured for x86_64-pc-linux-gnu [...] Interfaces supported: X11 External libraries:

>>>>> Viechtbauer, Wolfgang (NP) writes: > Hi all, > Just noticed that the error that arises when calling t.test() with factors could be a bit clearer: >> t.test(factor(c(3,1,2,4,3,5,4,5)), factor(c(2,1,2,3,4,5))) > Error in var(x) : Calling var(x) on a factor x is defunct. > Use something like 'all(duplicated(x)[-1L])' to test for a constant vector.

Dear Dushanthi, Please keep your e-mails on the R-Help list, where Michael has already given you some excellent advice. As Michael already explained, metafor can handle proportions, but does not have any specific functionality for categorical variables with more than 2 levels (at the moment). So, if it is logical and possible to do so, you could collapse the levels of the categorical outcome to 2

Dear All, A while back, the question was raised whether R would run on an Eee PC: http://tolstoy.newcastle.edu.au/R/e3/help/07/12/6564.html There were some positive responses and some suggestions for getting this to work: http://tolstoy.newcastle.edu.au/R/e3/help/07/12/7244.html For those who would like a step-by-step guide, here it is. I hope somebody might find this useful. 1) open up a

Dear All, I have a question about formulas and model.matrix(). If one specifies a model via a formula, the corresponding design matrix can be obtained with the model.matrix() function. For example: x1 <- c(1,4,2,3,5) x2 <- c(1,1,2,2,2) myformula <- ~ x1 + factor(x2) model.matrix(myformula) My question is: If an intercept term is in the model (like in the example above), is it always

>>>>> "VW" == Viechtbauer Wolfgang (STAT) <Wolfgang.Viechtbauer at STAT.unimaas.nl> >>>>> on Fri, 26 Sep 2008 18:00:19 +0200 writes: VW> Hi all, I'm trying to fit a marginal (longitudinal) VW> model with an exponential serial correlation function to VW> the Orange tree data set. However, R crashes frequently VW>

Hello All, Despite my preference for reporting confidence intervals, I need to obtain a p-value for a hypothesis test in the context of regression using bootstrapping. I have read John Fox's chapter on bootstrapping regression models and have consulted Efron & Tibshirani's "An Introduction to the Bootstrap" but I just wanted to ask the experts here for some feedback to make

A new package is now available via CRAN, called metafor. The metafor package consists of a collection of functions for conducting meta-analyses in R. Fixed- and random-effects models (with and without moderators) can be fitted via the general linear (mixed-effects) model. For 2x2 table data, the Mantel-Haenszel and Peto's method are also implemented. The package also provides various plot

Dear expeRts, I fail to succesfully pass strings to functions. It comes down to the observation that > plot(someVariable,anotherVariable) works fine, but > x <- "someVariable" > y <- "anotherVariable" > plot(x,y) does not. Does this have something to do with the returned value of x being /"someVariable"/ and not /someVariable/, i.e.

Hi, I have been looking for an R package which allowed to do meta-analysis (both pairwise and network/mixed-treatment) at arm-level rather than at trial-level, the latter being the common way in which meta-analysis is done. By arm-level meta-analysis I mean one that accounts for data provided at the level of the individual arms of each trial and that does not simply derive the difference between

Ok.. munging the tag below to get pas the agressive mailbot administrivia filter. I have a manifest the following: module::foo{"$someVariable": param1=>"x" } modul::bar{"data": 5ubscribe => [Module::Foo["$someVariable"]] } The only way to get past the parsing seems to be to do one of the following: 5ubscribe

Hello all, I am using forest.rma to plot a random effects model meta-analysis. I noticed that refline sets a vertical line indicating the null hypothesis. Is there a way to draw another vertical line, possibly dashed, centered on the summary estimate? Prof. Viechtbauer, if you happen to read this, I'd like to thank you for making an excellent package. I have been using the metafor package

Hi I'm conducing a meta-analysis using the meta package. Here's a bit of code that works fine - tmp <- metacont(samplesize.2, pctdropout.2, sddropout.2, samplesize.1, pctdropout.1, sddropout.1, data=Dataset, sm="WMD") I would now like to control for a couple of variables (continuous and categorical) that aren't in the equation. Is meta

I'm trying to set a channel variable and make it available to another channel: I thought that if I SetVar(_SomeVariable=SomeValue) or SetVar(__SomeVariable=SomeValue) then SomeVariable would be available in the destination channel. However __SomeVariable, _SomeVariable and SomeVariable are all blank. The scenario: Agents logon to the queue using callbacklogin. From what I can gather

Dear Wolfgang Viechtbauer and list members: I have discovered your "MiMa" function for fitting meta-analytic mixed-effects models through an earlier discussion on this list. I think it is extremely useful and fills an important gap. In particular, since it is programmed so transparently, it is easy to adapt it for one's own needs. (For example, I have found it easy to identify

Often it is useful to keep a "codebook" to document the contents of a dataset. (By "dataset" I mean a rectangular structure such as a dataframe.) The codebook has as many rows as the dataset has columns (variables, fields). The columns (fields) of the codebook may include: ? variable name ? type (character, factor, integer, etc) ? variable label