similar to: sorting in lmList object

Dear List, I am plotting lmList objects using plot(intervals()) in nlme package. I want to make changes to the y-axis labels. When I try to change cex of y-axis labels using the following: fm1 <- lmList(distance ~ age | Subject, Orthodont) plot(intervals(fm1), scales=list(y=list(cex = .7))) I receive: Error in bwplot(formula = group ~ intervals | what, data = structure(list( : formal

Dear R-devel members, I think I've found a minor bug in plot.intervals.lmList. ( The guide https://www.r-project.org/bugs.html suggests to report it here, as I do not have a bugzilla account.) Here is a minimal reproducible example to demonstrate the problem: fm1 <- lmList(distance ~ age | Subject, Orthodont) plot(intervals(fm1),ylab="a") This results in: "Error in

Dear colleges, I would like to use the lmList function. I have installed the lme4 library but when I try to use the lmList function I get this error message. Error: could not find function "lmList" Here you can see what kind of messages I am getting when installing lme4 package. Does anyone know how to solve this problem? Thanks Rosario > install.packages() --- Please select a

I'd like to fit a GLM to each of a number of subsets of some data. The `family' argument to `lmList' (in lme4) has given me cause for optimism, but so far I've only been able to achieve linear model fits. For example > df <- data.frame(gp = gp.temp <- factor(rep(1:3, each = 100)), x = x.temp <- rnorm(300), y = rpois(300, exp((-1:1)[gp.temp] + x.temp))) Then a call to

Hello, I installed the newest version of R (3.0.2) as well as the newest version of nlme (3.1-113) in order to use summary.lmList and other nlme functions. Once loading the new library, lmList and summary.lm can be found, but a number of additional functions cannot be found via command. Versions installed and loaded are correct. Any suggestions on how to allow for these functions of the new

Hello, in R-2.1.0 I'm trying to prodice trellis plots from an lmList object as described in the help for plot.lmList. I can generate the plots from the help, but on my own data plotting fails with an error message that I cannot interpret (please see below). Any hints are greatly appreciapted. kind regards, Arne > dim(d) [1] 575 4 > d[1:3,] Level_of_Expression SSPos1 SSPos19

Dear all, I've got a problem in including square variables in lme and lmlist functions. I've tried to work on Oxboys data of Pinheiro and Bates'book, which consist of the heights of 26 boys, each mesured on nine different occasions : > Oxboys Grouped Data: height ~ age | Subject Subject age height Occasion 1 1 -1.0000 140.50 1 2 1 -0.7479 143.40

Dear Martin, Have you try to create a new variable for age squared, say agesq? If you fit the model using this new variable you should get the coefficients. So your new model is something like height~age+agesq I hope this helps, Saghir > -----Original Message----- > From: MARTIN Ludovic [SMTP:martinl@mathinfo.ens.univ-reims.fr] > Sent: Wednesday, 07 May, 2003 2:02 PM > To:

I'm having trouble understanding how functions in the subset argument for lmList search for the objects they need. This trivial example produces "Error in rownames(fakedf) : Object "fakedf" not found": library(nlme) fitbyID <- function() { fakedf <- data.frame(ID = gl(5, 10, 50), A = sample(1:100, 50), B = rnorm(50))

Howdee, *** I know that the lmList() function exists, yet I don't want to use it. *** Would anyone be kind enough to tell how I can apply the function lm() to each level of a given factor so to obtain the intercept and slope for each factor level within a matrix? For instance, suppose a dataframe containing 3 variables: id, x and y. I want to compute the function lm() for each level

Hi R-helpers. #I start with the reproducible example: firm<-c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10)) year<-c(rep(1998:2007,5)) industry<-c(rep(1,20),rep(5,10),rep(7,10),rep(9,10)) X1<-rnorm(50) X2<-rnorm(50,mean=0.5,sd=0.1) Y<-rnorm(50,mean=0,sd=0.5) data<-data.frame(firm, industry,year,X1,X2,Y) data #I need to calculate for all the industries the following

Am I trying to perform multiple linear regressions on each 'VARIABLE2'. I figured out that there are different ways, using the following code: (data is given at the end of this message) reg <- lapply(split(TRY, VARIABLE2), function(X){lm(X2 ~ X3, data=X)}) lapply(reg, summary) Which produces the following: $`1` Call: lm(formula = X2 ~ X3, data = X) Residuals: Min

Hi r-helpers! I need to save the output of summary() function that I?ve runned like this: z<- lmList(y~x1+x2| x3, na.action=na.omit,data1,subset=year==1999) w<-summary(z) The output (w) is something like this: Call: Model: y ~ x1 + x2 | x3 Data: data1 Coefficients: (Intercept) Estimate Std. Error t value Pr(>|t|) 1 0.081110514 1.141352e-01

Dear all, I have a question on handling of missing values in lmList. My data set have continuous predictor and response, x and y, and a grouping variable group.id. All these variables have NAs and the data set also has several other variables that also contains NAs. To create the lmList-object seems to work fine: y.list <- lmList(y ~ x | group.id, data=mydata, na.action=na.omit) However,

NB: Not reply needed (Ben was extremely helpful!) I've just started using R last week and am still scratching my head. I have a data set and want to run a separate regression across each level of a factor (treating each one separately). The data right now is arranged such that the value of the factor along which I want to "split" my data is one column among many. Best way to do

Hi list, Using the lmList function from ?nlme package? I get the following error message: ?Error in !unlist(lapply(sum.lst, is.null)) : invalid argument type? # this is the syntax used # fm_cream <-lmList(MULTDV~TIME|cod, data=zz, na.action=na.omit) # summary(fm_cream) When I generate a simple example the function works, but on the real data I get that message. I imagine that it is a

Dear List: I have a data set with over 7000 students with about 4 observations over time per student. I want to examine the within-group fits of a random sample of this group as it takes forever to compute and draw all 7000 regressions. Here is the code I have used so far. >group<-groupedData(math~year|childid, data=scores) >group.list<-lmList(group)

Dear r-helpers, Can anyone suggest why lm() doesn't complain here: summary(osss.lm1 <- lm(logOdds ~ c.setSize %in% task, data = osss)) whereas in package:nlme (and in package:lme4) osss.lmL <- lmList(logOdds ~ c.setSize %in% task | subj, data = osss) # Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : # contrasts can be applied only to factors with 2 or more

Over on StackOverflow someone is trying to get this code to work: library("nlme") fm2Pixel.lis<-lmList(pixel~day+I(day^2)|Dog, Pixel) summary(fm2Pixel.lis) (results: Error in `[<-`(`*tmp*`, use, use, ii, value = lst[[ii]]) : subscript out of bounds) http://stackoverflow.com/questions/32680306/plotting-individual-confidence-intervals-for-the-coefficients-in-the-lmlist-fit

Greetings all, Is there a way to do the equivalent of a lmList (fit separate models for each subject) in the package nlme for a glm? Thank you very much, Peter B. [[alternative HTML version deleted]]