Dear Thierry id.pat = rep(seq(1:nsample), each =n.longitudinal.observations)
time = rep(seq(1:n.longitudinal.observations)-1, nsample) age = rnorm(nsample, mean = 36, sd = .8) f.age = table(cut(age, breaks = 8)) id.age = rep(f.age, each =5) visit = rnorm(nsample, mean = 2, sd = .03) f.visit = table(cut(visit, breaks = 3)) id.visit = rep(f.visit, each =5) 1. I was able to solve the age problem and the number of visits problem. Now the problem is another: yy~1+id.age+time+(time|id.pat) or yy~1+id.age + time+(time|id.pat) + (1|id.visit) there is no problem, but when I perform LMER, for example: lmer(yy~1+id.age+time+(time|id.pat)), there are errors: Error in model.frame.default(drop.unused.levels = TRUE, formula = yy ~ : variable lengths differ (found for 'time’) or Error in model.frame.default(drop.unused.levels = TRUE, formula = yy ~ : variable lengths differ (found for 'id.age') 2. I wasn’t trying to add the same variable to both random and fixed effects. I’m simulating a model and I’m trying to figure if it makes sense to add some variables into the model. Another doubt, 3. LMER only accepts categorical variables? Best, RO Atenciosamente, Rosa Oliveira -- ____________________________________________________________________________ Rosa Celeste dos Santos Oliveira, E-mail: rosit...@gmail.com Tlm: +351 939355143 Linkedin: https://pt.linkedin.com/in/rosacsoliveira ____________________________________________________________________________ "Many admire, few know" Hippocrates > On 11 Aug 2015, at 09:00, Thierry Onkelinx <thierry.onkel...@inbo.be> wrote: > > Dear Rosa, > > 1) use cut() to convert a continuous variable into a factor. See ?cut for the > details. > 2) The syntax for factors is the same as for continuous variables. Just add > the name of the factor variable to the formula > fAge <- cut(age) > yy~1+fAge+time+(time|id.pat) > 3) Add + (1|fAge) to the formula. Note that adding fAge to both the fixed and > the random effect doesn't make sense. > yy~1+time+(time|id.pat) + (1|fAge) > > Best regards, > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature and > Forest > team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance > Kliniekstraat 25 > 1070 Anderlecht > Belgium > > To call in the statistician after the experiment is done may be no more than > asking him to perform a post-mortem examination: he may be able to say what > the experiment died of. ~ Sir Ronald Aylmer Fisher > The plural of anecdote is not data. ~ Roger Brinner > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of data. ~ > John Tukey > > 2015-08-11 1:44 GMT+02:00 Rosa Oliveira <rosit...@gmail.com > <mailto:rosit...@gmail.com>>: > > > ############################################################################### > > # Clear memory and set the working directory and the seed > > ############################################################################### > > rm(list = ls()) > > setwd("/Dropbox/LMER/R ") > > set.seed(7010) > > ############################################################################### > > # Load up needed packages and do a require > > ############################################################################### > > # install.packages("gdata") > > > > library(nlme) > > library(lme4) > > > > nsample = 1000 # > Number of subjects > > n.longitudinal.observations = 5 # number of > observations per subject > > > > ############################################################################### > > # Set the other parameters > > ############################################################################### > > id.pat = rep(seq(1:nsample), each > =n.longitudinal.observations) > > time = rep(seq(1:n.longitudinal.observations)-1, > nsample) > > age = rnorm(nsample, mean = 36, sd = .8) > id.age = rep(seq(1: n.longitudinal.observations), each > =age) > > > > > > ############################################################################### > MODEL WITHOUT AGE > > boldBeta_individual_blup = coef(lmer(yy~1+time+(time|id.pat) ))$id.pat > #mixed model > > > > > > ############################################################################### > MODEL WITH AGE > > boldBeta_individual_blup = coef(lmer(yy~1+age+time+(time|id.pat) ))$id.pat > #mixed model > > > > Dear all, > > > > > > I’m trying to use LMER in my simulation problem, and I’m having problems ate > the very begging L I’m new in LMER. Can you please help me? > > > > > > 1st problem: > > how do I generate age so I can use it as a fixed factor? > > 2nd problem: > > how do I insert age as a fixed factor? > > 3rd problem: > > what if I wanted to insert a 2nd random effect based on age? > > > > Best, > > RO > > > > Atenciosamente, > Rosa Oliveira > > -- > ____________________________________________________________________________ > > > Rosa Celeste dos Santos Oliveira, > > E-mail: rosit...@gmail.com <mailto:rosit...@gmail.com> > Tlm: +351 939355143 <tel:%2B351%20939355143> > Linkedin: https://pt.linkedin.com/in/rosacsoliveira > <https://pt.linkedin.com/in/rosacsoliveira> > ____________________________________________________________________________ > "Many admire, few know" > Hippocrates > > ______________________________________________ > R-help@r-project.org <mailto:R-help@r-project.org> mailing list -- To > UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > <https://stat.ethz.ch/mailman/listinfo/r-help> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > <http://www.r-project.org/posting-guide.html> > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
