similar to: multiple GLMs with lmList in lme4

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

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:

Hi all, Forgive me if this is an obvious one.... I want to make a plot of confidence intervals from an lmList object with a collection of simple linear models (lm(y~x)) using: plot(intervals(mylmList)) and sort the plot by increasing mean values for the intercept. Is there an easy way of doing this? I've tried the "order()" and "sort.list()" functions, but I suspect

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

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 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

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

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

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]]

Hello R-Helpers, I was trying to use the lmList function to get the lmList graphic similar to Pinheiro and Bates (pg 33). I did not have a problem creating the graphic when I used the Orthodont data frame or 2 other data sets when there are no missing values. My data has missing values. Do I need to remove the missing values before the lmList function will work? for a small example: > a

Hello, I am trying to use lmLists in the lme4 package and copying over very standard code from the nlme package given in 'Mixed-Effects Models in S and S-Plus'. It appears to not accept an 'I(age-11)' in the formula, though it will accept the formula with out the subtraction of 11 from age. This seems like it would be a bug, since this is standard formula syntax, unless

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,