similar to: getting variable names into formulas

I have a factor (with "n" observations and "k" levels), with only "nobs" < n of the observations not missing. I would like to produce a (n x k) model matrix with treatment contrasts for this factor, with rows of NAs placeholding the missing observations. If I use model.matrix() I get back a (nobs x k) matrix. Is there an easy way to get the (n x k) without

Hello, I have a simulated data structure in which students are nested within teachers, and with each student are associated two test scores. There are 20 classrooms and 25 students per classroom, for a total of 500 students and two scores per student. Here are the first 10 lines of my dataframe "d": studid tchid Y time 1 1 1 -1.0833222 0 2 1 1

I may be missing something obvious here, but consider the following simple dataset simulating repeated measures on 5 individuals with pretty strong between-individual variance. set.seed(1003) n<-5 v<-rep(1:n,each=2) d<-data.frame(factor(v),v+rnorm(2*n)) names(d)<-c("id","y") Now consider the following two linear models that provide identical fitted values,

Often I perform the same task on a series of variables in a dataframe, by looping through a character vector that holds the names and using paste(), eval(), and parse() inside the loop. For instance: thesevars<-names(environmental) environmental$ToyOutcome<-rnorm(nrow(environmental)) tableOfResults<-data.frame(var=thesevars) tableOfResults$Beta<- NA

Greetings, I have a meta-analysis problem in which I have fixed effects regression coefficients (and estimated standard errors) from identical models fit to different data sets. I would like to use these results to create pooled estimated regression coefficients and estimated standard errors for these pooled coefficients. In particular, I would like to estimate the model \beta_{i} = \mu +

Dear Lockwood, As you can see, I'm a beginner... But thank you very much! Sincerely, Tord Quoting "J.R. Lockwood" <lockwood at rand.org>: > how about > > buskartant$buskartant <- sapply( group.list, function(x) > sum(!is.na(unique(x))) ) > > OR > > buskartant$buskartant <- sapply( group.list, function(x) > length(unique(x[!is.na(x)])) )

Dear all, I have partial data set with four colums. First column is "site" with three factors (i.e., A, B, and C). From second to fourth columns (v1 ~ v3) are my observations. In the observations of the data set, "." indicates missing value. I replaced "." with NA. To replace "." with NA, I used two steps. First, I replaced "." with NA, and

Dear r-users, Basically, I have a data as follows, > data S s1 s2 s3 s4 s5 prob obs num.strata 1 NNNNN N N N N N 0.0000108 32 <NA> 2 NNNNY N N N N Y 0.0005292 16 <NA> 3 NNNYN N N N Y N 0.0005292 24 <NA> 4 NNNYY N N N Y Y 0.0259308 8 1 .... I want to replace <NA> by 0, when I tried the following

Greetings, This seems too rudimentary to ask but for the life of me I cannot locate a readily easy method to compute the univariate mode. I know "mode" is not correct and "table" provides a reasonable count but I figured there would be an easy way to extract the value from the table after I do something like: max(table(mydadat$myvar)) unfortunately it only returns the max

Can a single random number be generated in R? I have an exercise that wants to simulate coin tosses, and I cannot seem to find a good example of the use of random number generation in R. Any help? Joshua Gramlich Chicago, IL

Hi all; This is my first message to the list, and I've got three "basic" questions: How could I insert comments in a file with commands to be used as source in R? Is it possible to quickly display a window with all the colors available in colors()? How? I'm displaying points, but they overlap, wether points() uses triangles, bullets or whatever. Is it possible to change

Hi everyone, I have a data frame Gene with SNPs eg. P1 P2 P3 CG CG GG -- -- AC -- AC CC AC -- AC I tried to replace all the GG with a value 3. Gene[Gene=="GG"]<-3 It always give me: Warning in `[<-.factor`(`*tmp*`, thisvar, value = 3) : invalid factor level, NAs generated Does any know if there is anything wrong with my code? Thanks, Zhengyu

without having to check the vector element by element? Thanks a lot! Jason ===== Jason G. Liao, Ph.D. Division of Biometrics University of Medicine and Dentistry of New Jersey 335 George Street, Suite 2200 New Brunswick, NJ 08903-2688 phone (732) 235-8611, fax (732) 235-9777 http://www.geocities.com/jg_liao

I want to subset the dataframe based on certain values in a row. for each row in my dataframe if ANY one value of a particular set of columns satisfies cond append a logical value true at the end of the row else append a false at the end of the row in the end I want to be able to subset the whole data based on the appended true or false value. I could literally code like this, but I think

If you found my subject heading to be confusing then I'm sure you'll enjoy the example I've included below. I find the apply type functions to be wonderful for avoiding loops but when I use them with existing functions, I end up using loops anyway to extract the vectors I want. I would appreciate it if someone could show me how to avoid these loops. Thanks. EXAMPLE:

Dear listers, I can't find the variance or se of the coefficients in a multilevel model using lme. I want to calculate a Chi square test statistics for the variability of the coefficients across levels. I have a simple 2-level problem, where I want to check weather a certain covariate varies across level 2 units. Pinheiro Bates suggest just looking at the intervals or doing a rather

In general this is what "apply" does. In your example you could use rowMeans(ar) as well, I think. Reid Huntsinger -----Original Message----- From: Olivier Martin [mailto:olivier.martin at inrialpes.fr] Sent: Tuesday, July 02, 2002 10:55 AM To: r-help Subject: [R] mean and array Hi all, I have an array, one say ar, with 3 dimensions. dim(ar) >200 3 4 I would like to

Hi Helpers: I have a factor object that has 314k entries of 39 land cover types. (This object can be coerced to characters neatly should that be easier to work with.) > length(foo) [1] 314482 > foo[1:10] [1] Montane Chaparral Barren Red Fir Red Fir [5] Red Fir Red Fir Red Fir Red Fir [9] Red Fir Red Fir 39 Levels:

Dear all, Sorry to bother you with one more newbie question. I have a dataobject with several hundreds of columns. I want to remove columns with a mean of the column values below a certain value: > a<- c(1,2,3,4,5,6) > b<-c(2,4,6,8,10,12) > c<- c(3,6,9,12,15,18) > test<- as.matrix(cbind(a, b, c)) > mean(a) [1] 3.5 > mean(b) [1] 7 > mean(c) [1] 10.5 Say the

Dear all, I observed that the R process is growing in time (I was working with the same session for two days, and the size reached 300 Mb). Explicit calls to 'gc()' did show a trigger around 90 Mb but did not change the RSS (while I remembered that my linux was nicely behaving before and the process size was shrinking when R was freeing memory...). I ended up saving the session, ending it