similar to: Fitting particular repeated measures model with lme()

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'm trying to fit a special kind of proportional odds model from: Whitehead et al. (2001). Meta-analysis of ordinal outcome using individual patient data. Statistics in medicine 20: 2243-2260. (model 2) The data are as follows: library(nlme) library(geepack) library(Design) library(MASS) options(contrasts=c("contr.SAS","contr.poly")) counts <-

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 +

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

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

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

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

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

Hi all, I have some difficulties with the lme function and so this is my problem. Supoose i have the following model y_(ijk)=beta_j + e_i + epsilon_(ijk) where beta_j are fixed effects, e_i is a random effect and epsilon_(ijk) is the error. If i want to estimate a such model, i execute >lme(y~vec.J , random~1 |vec .I ) where y is the vector of my data, vec.J is a factor object

It seems that glances is not in EPEL for CentOS 8. Is that coming at some point, or has it been deprecated in favor of some other tool?

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:

Hi R-helpers, I'm new to time series modelling, but my requirement seems to fall just outside the capabilities of the arima function in R. I'd like to fit an ARMA model where the variance of the disturbances is a function of some exogenous variable. So something like: Y_t = a_0 + a_1 * Y_(t-1) +...+ a_p * Y_(t-p) + b_1 * e_(t-1) +...+ b_q * e_(t-q) + e_t, where e_t ~ N(0, sigma^2_t),

Dear R-users Coming from a proc mixed (SAS) background I am trying to get into the use of (n)lme. In this connection, I have some (presumably stupid) questions which I am sure someone out there can answer: 1) With proc mixed it is easy to get a hold on the estimated variance parameters as they can be put out into a SAS data set. How do I do the same with lme-objects? For example, I can see the

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

Dear All, I have a model to predict time series data for example: data(LakeHuron) Lake.fit <- arima(LakeHuron,order=c(1,0,1)) then the function predict() can be used for predicting future data with the model: LakeH.pred <- predict(Lake.fit,n.ahead=5) I can see the result LakeH.pred$pred and LakeH.pred$se but I did not see residual in predict function. If I have a model: [\ Z_t =

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

Hello R-users, I need to create a vector inserting an 1 after each value of another vector. For example: vec1<-c(2,3,4) I need to create a vector with the values 2,1,3,1,4 Does anyone know how create this vector without loops (vec1 could have 1000 elements) Thank you, Juan -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read