Re: [R] model non-nested random effects in nlme library
Season Individual FT FTLengthCurvIndex dir.lin 2009W GW522 1 20 0.538931977 1.8884631 2009W GW522 2 28 0.498651384 0.8379838 2010W A1841 17 0.492549537 1.23907 2010W A1842 23 0.630582873 1.3010501 2010W A1843 27 0.478359129 0.6488715 2010W OO456 1 19 0.533888959 2.1471811 2011S A1421 5 0.777146676 2.1168675 2011S A1422 9 0.875245592 1.6422436 2011S A1423 7 0.912760026 1.7903588 2011S A1424 8 0.368177237 1.8827868 2011S A1425 12 0.790110963 1.723052 2011S A1426 17 0.530349103 2.104049 2011S GW503 1 9 0.822049259 1.1624394 2011S GW503 2 9 0.805705677 1.4590542 2011S GW503 3 8 0.764926849 1.3209942 2011S GW503 4 6 0.802072344 1.3903048 2011S GW503 5 11 0.651539153 1.8380583 2011S GW503 6 10 0.830663679 1.588408 2011S A1881 9 0.710436628 1.648512 2011S A1882 9 0.718584921 1.8092618 2011S A1883 11 0.641348724 1.6436084 2011S A1884 13 0.68348373 1.9246773 2011S A1885 16 0.652572155 1.8031925 2011S LB504 1 8 0.852924101 1.3636355 2011S LB504 2 13 0.823136776 1.4618325 2011S LB504 3 12 0.75605543 1.3690891 2011S LB504 4 18 0.478978335 1.4824566 2011W A1681 14 0.281223063 0.9328787 2011W LB491 1 16 0.610471298 1.968323 2011W LB491 2 19 0.510918052 1.4519552 2011W LB491 3 22 0.503229145 0.8539206 2011W LB491 4 50 0.538715522 0.9241864 2011W OO440 1 17 0.565258152 1.7838117 2011W OO440 2 33 0.561548705 1.0129331 2011W OO440 3 67 0.272020469 0.4717046 2009W GW495 1 36 0.501137969 1.5722404 2009W FB515 1 37 0.573009216 -1.6528193 2009W FB513 1 25 0.63702884 -2.0009436 2009W FB513 2 117 0.393231124 -1.213341 2010W A1641 27 0.734281437 1.3515392 2010W A1642 48 0.46142686 0.8394697 2010W A1643 32 0.649801375 0.8179546 2010W OO455 1 22 0.697236934 1.8904179 2010W OO455 2 20 0.458066447 2.7011468 2010W OO455 3 31 0.406230997 2.3547132 2010W OO478 1 28 0.666138495 1.6501422 2010W OO478 2 36 0.682536815 1.5002367 2010W OO478 3 12 0.545977976 1.264352 2010W OO478 4 57 0.408892851 0.8349835 2010W A1601 36 0.744976923 1.2087431 2010W A1602 47 0.552217128 0.8730726 So here I have copied a small subset of my data. It has to do with seals swimming to and from an island to forage as obtained from sattelite telemetry data. Season is 2009W (2009 winter), 2011s = 2011 summer etc. Then there is individual. FTLength is foraging trip length...i.e. how many days the animal was out to sea. FT is the number of foraging trip. I.e. the first or the second. CurvIndex is what I call the curvilinear index...which basically measures how straight or loopy the animal travels to and from the island. This is my independent variable and varies between 0 and 1, where 1 is straight and 0 is very undirectional...or "loopy" and then dir.lin is the mean direction from the island which was a circular variable but I converted to a linear one. So I basically want to model the following: lmer(Curvindex~FTLenght+FT+dir.lin + (1|Individual) + (1|Season) I used Individual and Season as seperate random effects because although I have repeated measurements for some individuals, they are within a year and no individual was tracked in more than one year. You said in your previous message that if I have good and bad years I might want to nest individual in year. Well since I only have 3 years, I dont think its really that feasible...or what I know from the data...none of the years were particularly different from the rest or "bad" in a sense. Is my thinking correct? How would you model my above example in the nlme library? Thanks again -- View this message in context: http://r.789695.n4.nabble.com/model-non-nested-random-effects-in-nlme-library-tp4321021p4321650.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list 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.
Re: [R] model non-nested random effects in nlme library
mwege gmail.com> writes: > > Hello all, > > In lme4 if you want to model two non-nested random effects you code it like > this: > > mod1 <- lmer(y~x + (1|randomvar1) + (1|randomvar2)) > > How would you go about to model something similar in nlme? > > In my database I have two variables for which I have repeated measures, lets > call them "individual" and "year". > But none of the "individuals" were measured in more than one year. So as I > understand it, I should not nest individual in year or visa versa. Not necessarily. If you believed that there were good years and bad years but individuals varied randomly within years (i.e. there is no such thing as a consistently good individual) then you would have individuals nested within years. If you have at least some multiple measurements of some individuals *within* some years, then you have a three-level model (samples within individuals within years, where the among-sample variance is the residual error); otherwise you have a two-level model (individuals within years). If you believe there are good individuals and bad individuals but that years are not good or bad for everyone then you have years nested within individuals. Otherwise you indeed have a crossed design. > Someone suggested I do it as above. But I am accustomed to nlme, and dont > know how one would code non-nested random effects. > > In the Pinheiro and Bates book there is an example coded like this: > modB <- lme(y~x, > + random = pdBlocked(list(pdIdent(~year-1), pdIdent(~individual-1 > > But when I try it I keep getting an error message saying: "Error in > getGroups.data.frame(dataMix, groups) : > Invalid formula for groups" It would definitely be best to forward this question to the r-sig-mixed-models r-project.org mailing list ... (I'm answering via Gmane, otherwise I would do it myself) Can you provide a reproducible example? __ R-help@r-project.org mailing list 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.
