Dear Diego, Please keep the mailing list in cc. You can turn off HTML posting in the settings of your mail editor. The problem with your model is that the random slope with a factor requires a variance-covariance matrix with the same dimension as the number of levels of the factor. In your case this requires 3079 parameters, just for the random effects. You would need observations for most of the species - year combination which you clearly don't have. So you model is too complex given the data. Here a a few solutions. 1) use a nested random effect of species within year: ~1|YearFound/Species 2) use a nested random effect of year within species: ~1|Species/YearFound 3) use crossed random effects using lme4 lmer(Lat ~ Killed + (1 | Species) + (1| YearFound)) Another option would be to model the probability of getting killed by latitude. glmer(Killed ~ Lat + (1 | Species) + (1| YearFound), family = binomial) 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 2016-09-13 10:08 GMT+02:00 Diego Pavon <diego.pavonjordan at gmail.com>:
Hello
Thanks for the reply. First, I did not know I was posting in HTML... How
can I do it otherwise (plain text like now)?
So, I want to asses whether the Latitude of ring recovery is related to
whether the bird was shot (killed) or not. I have recoveries from 1914 to
2014. Then I thought to use 'Year' (i.e. when the ring was recovered) as a
random intercept and, since I am using multiple species, use 'species' as a
random slope. The code looks like this:
model1 <- lme(Lat ~ Killed, random =~ 1 + Species | YearFound, #Year =
random intercept, Species = random slope
method = "REML",
data = Rings2)
Killed has two levels (killed or not killed),
Year has 100 levels (1913-2013) and
species has 56 levels (56 different species included). We have selected
species with >= 10 observations (recoveries).
Or can I even do this? Would I need observations in all years?
By the way, I am using RStudio Version 0.99.903 and R-64 3.2.2 on Windows
7 (RAM 8GB).
Thanks!
Diego
2016-09-13 10:36 GMT+03:00 Thierry Onkelinx <thierry.onkelinx at inbo.be>:
Dear Diego, Please don't post in HTML. Can you provide more information on the model and the data? What is the formula of the model (fixed and random). Type of the variables. In case of factors: the number of levels. How many observations/groups do you have? 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 2016-09-13 8:18 GMT+02:00 Diego Pavon <diego.pavonjordan at gmail.com>:
Dear colleagues I am handling a (relatively large) data set on ring recoveries and I want to fit a random effects model to the data using the package lme. When I run the RANDOM INTERCEPT ONLY model it runs nicely, but when I try to include also RANDOM SLOPE then I get an error message: Error in logLik.lmeStructInt(lmeSt, lmePars) : 'Calloc' could not allocate memory (2036500788 of 8 bytes) My memory is right now:
memory.size()
[1] 375.64
memory.limit()
[1] 3e+11 I have tried to run it only with R running in the computer (plus the basic stuff that may use RAM) but still can't get the results. Any ideas how to deal with this issue? THANK YOU VERY MUCH! Di -- *Diego Pav?n Jord?n* *Finnish Museum of Natural History* *PO BOX 17 * *Helsinki. Finland* *0445061210https://tuhat.halvi.helsinki.fi/portal/en/persons /diego-pavon-jordan%288d5db37c-eddd-4fca-92cd-9c9956a42b4a%29.html <https://tuhat.halvi.helsinki.fi/portal/en/persons/diego-pav on-jordan%288d5db37c-eddd-4fca-92cd-9c9956a42b4a%29.html>htt p://www.linkedin.com/profile/view?id=170617924&trk=nav_respo nsive_tab_profile <http://www.linkedin.com/profile/view?id=170617924&trk=nav_r esponsive_tab_profile>https://helsinki.academia.edu/DiegoPavon <https://helsinki.academia.edu/DiegoPavon>* [[alternative HTML version deleted]]
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