similar to: fixed effects

Hello everyone! I would really appreciate it if someone knew where could I find the command in R in order to run a fixed effects regression. What format should my data have? I have looked through the manual and I could not find anything Thank you in advance, Petros [[alternative HTML version deleted]]

Hello all. I was wondering if the logLike.nls() and logLike.nlme() functions are still being used. Neither function seems to be available in the most recent release of R (1.9.1). The following is contained in the help file for logLik(): "classes which already have methods for this function include: 'glm', 'lm', 'nls' and 'gls', 'lme' and others in

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 R-Help, ----------------------------------------------------------------------------------------------------------------------------------------- Issues (there are 2): 1) Possible bug when using lmtest::encomptest() with a linear model created using nlme::lmList() 2) Possible modification to lmtest::encomptest() to fix confusing fail when models provided are, in fact, nested. I have

Dear r-helpers, After successfully running require(nlme) vfr.lmL <- lmList( estimate ~ (slant + respType + visField + hand)^2 | subject, vfr ) pairs(vfr.lmL, id = 0.01, adj = -0.5) # Pinheiro & Bates (p. 141) produces the following error: Error in sprintf(gettext(fmt, domain = domain), ...) : object "form" not found Any guesses as to what I may have done wrong?

Dear all, I am not fluent in R and am struggling to 1) apply a lm to a weight-size dataset, thus the model has to run separately for each species, each year; 2) extract coefs, r-squared, n, etc. The data look like this: year sps cm w 2009 50 16 22 2009 50 17 42 2009 50 18 45 2009 51 15 45 2009 51 16 53 2009 51 17 73 2010 50 15 22 2010 50 16 41 2010 50 16 21 2010

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))

I am using rw0641. In my continuing quest to understand repeated measures analysis, I again return to lme. I exported the Potthoff and Roy data Orthodont.dat from S-PLUS 4.5 to avoid capture errors and ran the examples in the R help. I imported the data.frame with data <- read.table("Orthodont.dat",header=T) attach(data) and created the objects Orthodont.fit1 <-

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

I'm using R 2.0.1. I looked in the email archives but didn't see anything on this topic. I've noticed a surprising (to me) difference between AIC and BIC: > methods("AIC") [1] AIC.default* AIC.logLik* > methods("BIC") [1] BIC.gls* BIC.lm* BIC.lme* BIC.lmList* BIC.logLik* BIC.nls* The BIC.gls BIC.lm BIC.lme BIC.lmList and BIC.nls functions appear

Inthe code below I was trying to to obtain the GMM estimates for CAPM (REGRESSION) for 36 stocks each have 180 observations,however it only gives me one output rather than 36. In SAS i would just put in a *By statement*. I have a variable TICKER that categorize them into 36 groups. *How can I obtain all 36 output instead of just one.* **

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

Hi, I'm experimenting with random effect natural splines, and I've encountered an odd problem. library(nlme); library(splines) a <- data.frame(x = 1:10, y = 1:10 + runif(10, min=-3, max=3), c = rep(c(1,2),5)) df <- 10 lml <- lmList(y ~ ns(x,df=df) | c, a) Error in df - 1 : non-numeric argument to binary operator I presume this is because the formula isn't evaluated

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

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 members of the R-Help Team, we are reaching out to you with a question regarding using intervals()<https://www.rdocumentation.org/packages/nlme/versions/3.1-163/topics/intervals> to create inference for nlme()<https://www.rdocumentation.org/packages/nlme/versions/3.1-164/topics/nlme> function. The maintainer for the nlme package is listed as the R-Core Team and we were advised

Hi, I am currently preparing a new version of my package papeR. When I run R CMD check using the development version of R I get the following note: Package in Depends field not imported from: ?nlme?, ?lme4?, ?survival? These packages needs to imported from for the case when this namespace is loaded but not attached. I now have problems to fix this issue. It is easy to get rid of two of the

Dea-R community. I'd like to draw your attention to an issue I have recently encountered while doing my current data analysis. I've got an unexpected (to me) result from the command: > augPred(lmList(my.object)), 'my.object' being a grouped data frame of class: > class(my.object) [1] "nfnGroupedData" "nfGroupedData" "groupedData"

Hello: Let me rephrase my question to attract interest in the problem I'm having. When I appply anova() to two equations estimated using glmmPQL, I get a complaint, > anova(fm1, fm2) Error in anova.lme(fm1, fm2) : Objects must inherit from classes "gls", "gnls" "lm","lmList", "lme","nlme","nlsList", or "nls"

Hi, While saving (function 'save') a 'lmList' object (pack nlme), R issues the warning messages: 1: namespaces may not be available when loading 2: names in persistent strings are currently ignored 3: namespaces may not be available when loading 4: names in persistent strings are currently ignored Any pitfall I should be aware of ? L. PS: I use > R.version _