similar to: odd behavior of summary()$r.squared

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

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 +

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

Hello, I have a dataframe with several hundred variables. I would like to explore updates of some baseline lme fit by including each of some subset of these variables, one at a time. For various reasons it is inconvenient to rely on the positions of the numbered columns in the dataframe. Here is what I want to do: mod.baseline<-lme(fixed=foo,data=dat,random=bar) for(thisvar in vars){

Jakob Stoklund Olesen <stoklund at 2pi.dk> writes: >> If we decide to spill r3, we call traceSiblingValue to find the original >> def (the load). After traceSiblingValue we have the load instruction to >> define r1 and the value number information for r3. We don't have the >> value information from r2 as far as I can tell. >> >> Is that correct?

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)])) )

On Sep 19, 2012, at 10:49 AM, <dag at cray.com> wrote: > Jakob Stoklund Olesen <stoklund at 2pi.dk> writes: > > So if there are multiple values between r2 and r3 (r2.1, r2.2, etc.) I > would just follow the chains implied by the SibValueInfo Deps array? > Basically, I want to find all of the live ranges related to r1. It really depends on what you're trying to do.

Hi, I have been using lm in R to do a linear regression and find the slope coefficients and value for R-squared. The R-squared value reported by R (R^2 = 0.9558) is very different than the R-squared value when I use the same equation in Exce (R^2 = 0.328). I manually computed R-squared and the Excel value is correct. I show my code for the determination of R^2 in R. When I do not set 0 as the

Jakob Stoklund Olesen <stoklund at 2pi.dk> writes: > On Sep 19, 2012, at 10:49 AM, <dag at cray.com> wrote: > >> Jakob Stoklund Olesen <stoklund at 2pi.dk> writes: >> >> So if there are multiple values between r2 and r3 (r2.1, r2.2, etc.) I >> would just follow the chains implied by the SibValueInfo Deps array? >> Basically, I want to find

On Sep 19, 2012, at 10:13 AM, dag at cray.com wrote: > The InlineSpiller in 3.1 is quite different from the old spiller so I am > trying to slog through the code and learn a bit. > > On a spill, the spiller calls traceSiblingValue. I gather that this is > supposed to find the "original" def point of a value, checking back > through copies, phis, etc. At the end we

I have several linear models on the same data: m1 <- lm(y ~ poly(x,1)) m2 <- lm(y ~ poly(x,2)) m3 <- lm(y ~ poly(x,3)) What I don't understand is why anova(m1, m2, m3, test="F") - yields the same RSS and SS values, but a different p-value from anova(m1, m2, test="F") - when it also yields the SAME as anova(m2, m3, test="F") What am I missing? Rob

Dear Members, I have two estimated transition matrices and I want to compare them. In fact I want to check the hypothesis if they come from the same process. I tried to look for some test but all I found was independence test of contingency tables. The following code shows that the usual chi-squared test statistic does not follow chisq distribution. MCRepl <- 5000 khi12 <- rep(0,MCRepl)

The InlineSpiller in 3.1 is quite different from the old spiller so I am trying to slog through the code and learn a bit. On a spill, the spiller calls traceSiblingValue. I gather that this is supposed to find the "original" def point of a value, checking back through copies, phis, etc. At the end we have an interval being spilled and the original def instruction of the value. For

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

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

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

Hi, I''m trying to get a handle on hfsc. Here is my configuration: root@jmnrouter:/jmn# tc class show dev vlan1 class hfsc 1: root class hfsc 1:1 parent 1: ls m1 0bit d 0us m2 225000bit ul m1 0bit d 0us m2 225000bit class hfsc 1:10 parent 1:1 rt m1 191000bit d 25.0ms m2 135000bit ls m1 0bit d 0us m2 135000bit ul m1 0bit d 0us m2 225000bit class hfsc 1:20 parent 1:1 rt m1 22008bit d