similar to: Mixed model

Hello all, I have problem with setting up random effects. I have a model: y=x1+x2+x1*x2+z1+z1*x2 where x1, x2, x1*x2 are fixed effects and z1, z1*x2 are random effects (crossed effects) I use library(nlme) 'lme' function. My question is: how I should set up random effects? I did lme(y~x1+x2+x1:x2, data=DATA, random=~z1+z1:x2, na.action='na.omit') but it did not work.

Hi All, I have conducted the following survival analysis which appears to be OK (thanks BRipley for solving my earlier problem). > surv.mod1 <- survreg( Surv(timep1, relall6)~randgrpc, data=Dataset, dist="weibull", scale = 1) > summary(surv.mod1) Call: survreg(formula = Surv(timep1, relall6) ~ randgrpc, data = Dataset, dist = "weibull", scale = 1)

Hi All., Following on from all the help I received earlier .. Just so as you know a well known text book (T&F) uses "repeated observations" - I think perhaps they meant repeated measures in retrospect I am a total beginer to ARIMA, but have read a a basic text. I read that ARIMA requires a minimum of 50 repeated measures in time (repeated measures)- Unfortunately, I have 8

Suppose this is my list of transactions: set.seed(200) tran=random.transactions(100,3) inspect(tran) items transactionID 1 {item80} trans1 2 {item8, item20} trans2 3 {item28} trans3 I want to get the 'transpose' of the data, i.e. transactionID items 1 {trans2} item8 2 {trans2} item20 3 {trans3} item28 4 {trans1} item80 I

Hello R-devel, Best wishes in the new year. I am writing to kindly request new R function so NA_real_ can be more easily detected. Currently if one wants to test for NA_real_ (but not NaN) then extra work has to be done: `is.na(x) & !is.nan(x)` Required functionality is already at C level so to address my request there is not that much to do. Kevin Ushey made a nice summary of current R C api

Hello, I can get the median for each factor, but I'd like another column to go with each factor. The nm column is a long name for the lvls column. So unique work except for the order can get messed up. Example: x =

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation

I'm having a problem with aggregate.formula when I call it in a function and the function is converted from a string in the funtion I think my problem may also only occur when the left hand side of the formula is cbind(...) Here is example code that generates a dataset and then the error. The first function "agg2" fails > agg2(FALSE) do agg 2 Error in m[[2L]][[2L]] : object

"nana" is meant to express "NA, really NA". Your suggestion sounds good. On Thu 2 Jan, 2020, 3:38 AM Pages, Herve, <hpages at fredhutch.org> wrote: > Happy New Year everybody! > > The name (is.nana) doesn't make much sense to me. Can you explain it? > > One alternative would be to add an extra argument (e.g. 'strict') to > is.na(). FALSE by

I'm working on an R package in C and can't seem to get the same level information about a factor that the R console displays. If I define a factor as: lvls <- factor(c('red','blue','blue','green','red'), c('blue','green','red'), ordered=TRUE) When I get the "levels" attribute in C, I get back the the first

Hi, Trying to learn Search::Xapian and be better at perl at the same time, I'm stuck, at the DB_CREATE_OR_OPEN error. Perl says this: ~/dev/sandbox/Xapian-perl$ ./Index1-Xap.pl 100-objects-v1.csv db "db" is not exported by the Search::Xapian module Can't continue after import errors at ./Index1-Xap.pl line 7. BEGIN failed--compilation aborted at ./Index1-Xap.pl line 7. What I

I have two factors l1, l2, and I'd like to merge them. (Remark: The factors can not be converted to charaters) Function c() does not give me the result I want: > l1 = factor(c('aaaa', 'bbbb')) > l2 = factor(c('ccc', 'dd')) > lMerge = factor(c(l1, l2)) > lMerge [1] 1 2 1 2 Levels: 1 2 > I'd like to merge l1 and l2 and to get lMerge

Dear CSAG R users, I will be glad if someone can point out what I am doing wrong or not doing at all in this. I am trying to write out netcdf file in R. I have 26 time step but only the first time step is written. For example: >library(ncdf) >path <- '/home/work/' >forecast <- open.ncdf(paste(path,'cam.1980.2005.nc',sep="")) > fore <-

Dear CSAG R users, I will be glad if someone can point out what I am doing wrong or not doing at all in this. I am trying to write out netcdf file in R. I have 26 time step but only the first time step is written. For example: >library(ncdf) >path <- '/home/work/' >forecast <- open.ncdf(paste(path,'cam.1980.2005.nc',sep="")) > fore <-

Dear List, Let's say I have a list whose components are 2 matrices (as exemplified in the "mylist" object below). I'd like to create a list with components being 4 matrices based on an logical index vector. is there a way to simplify what I'm doing to obtain the results in "mylist2"? I'd like something that would work on an arbitrary number of elements in

Inline. Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, Oct 14, 2020 at 3:23 PM 1/k^c <kchamberln at gmail.com> wrote: Is which() invoking c-level code by chance, making it slightly faster > on average? > You do not need

When I try to run the following non-linear regression with variables index1 and prl3: > beta = 4 > nls(index1~beta*(1/prl3),start = list(beta = 4)) I get this error message: Error in nls(index1 ~ beta * (1/prl3), start = list(beta = 4)) : REAL() can only be applied to a 'numeric', not a 'logical' I've got no clue as to the REAL() to which this is referring. Any

xtabs does this automatically if your cross classifying variables are factors with levels all the cities (sorted, if you like): > x <- sample(letters[1:5],8, rep=TRUE) > y <- sample(letters[1:5],8,rep=TRUE) > xtabs(~ x + y) y x c d e a 1 0 0 b 0 0 1 c 1 0 0 d 1 1 1 e 1 1 0 > lvls <- sort(union(x,y)) > x <- factor(x, levels = lvls) > y <-

Hi everyone, I have 2 environments (2 different R sessions) as described below: Session 1: Name of the environment: "CrlmmInfo" Objects in the environment: index1: logical index - length 238304 index2: logical index - length 238304 priors: list of 4 - (matrix 6x6, 2 vectors of length 6, vector of length 2) - all num params: list of 4: centers [238304 x 3 x