[R] Naming a random effect in lmer

[spencerg]

  I miscommunicated: In every application I've seen with large numbers 
of parameters to estimate, most of those parameters are specific 
instances of different levels of a random effect. For example, a 
colleague recently did a fixed effects analysis of a longitudinal 
abundance survey of a large number of species of wildlife. This 
colleague claimed that treating species as a random effect was 
inappropriate, because the species were not selected by use of random 
numbers. With only two or three species, if the scientists were only 
concerned with those two or three species, this may be reasonable.


However, most scientists -- and people who study their work -- will want 
to generalize beyond only the species in the study. Even if scientists 
were only interested in two or three species for which they had data, 
Stein's phenomenon suggests that even a rabid Bayesophobe would likely 
get lower mean square error at the expense of some bias from pretending 
the species were randomly selected from some larger population 
(http://en.wikipedia.org/wiki/James-Stein_estimator).


If I were asked to referee a paper or serve on a thesis committee for a 
study estimating 30 random effects, I would not be happy unless there 
were a convincing discussion of why it was appropriate to estimate all 
those random effects separately; right now, I can not imagine an 
application where that would be appropriate.


If you and your advisor still feel that what you are doing makes sense, 
I suggest you first get the source code via "svn checkout 
svn://svn.r-forge.r-project.org/svnroot/lme4" (or by downloading 
"lme4_0.999375-30.tar.gz" from 
"http://cran.fhcrc.org/web/packages/lme4/index.html"), then walk through 
the code line by line using the "debug" function (or "browser" or the 
"debug" package). From this, you will likely see either (a) how you can 
do what you want differently to achieve the same result or (b) how to 
modify the code so it does what you want.


Hope this helps.
Spencer


Leigh Ann Starcevich wrote:
> Here is a test data set and code. I am including the data set after 
> the code and discussion to make reading easier. Apologies for the size 
> of the data set, but my problem occurs when there are a lot of Z 
> variables. Thanks for your time.
>
> # Enter data below
>
> # Sample code
> library(lme4)
> mb<- length(unique(testsamp$WYear))
>
> # Create the formula for the set of identically distributed random 
> effects
> Zs<- paste("Z",2:(mb-1)),sep="")
> Trendformula <-as.formula(paste("LogY ~ WYear + (1+WYear|Site) + (1|", 
> randommodel=paste(paste(Zs,collapse="+"), ")")))
>
> fittest<-lmer(Trendformula, data = testsamp)
> summary(fittest)
>
> # Here I get an error because the name of the random effect is too 
> long to print
> # in the random effects output (I think).
> # The error message is: Error in names(bars) <- unlist(lapply(bars, 
> function(x)
> # deparse(x[[3]]))) : 'names' attribute [3] must be the same length as 
> the vector [2]
>
> # However, when fewer Z variables are used in the random portion of 
> the model,
> # there is no error.
> # Using only Z2 + … + Z9 for the random intercept
>
> Zs2<- paste("Z",2:9,sep="")
> Trendformula2 <-as.formula(paste("LogY ~ WYear + (1+WYear|Site) + 
> (1|", randommodel=paste(paste(Zs2,collapse="+"), ")")))
> fittest2<-lmer(Trendformula2, data = testsamp)
> summary(fittest2)
>
>
> # Is there a way to either name the set of iid random effects 
> something else or
> # to define a random variable that could be used in the model to create a
> # random intercept?
>
> # I have had some success in lme, but it would be helpful for my 
> simulation if I
> # could conduct this analysis with lmer. My model in lme is not correctly
> # estimating one of the variance components (random Site intercept).
> # I am using:
>
> detach(package:lme4)
> library(nlme)
> random.model.lme 
> <-as.formula(paste("~-1+",paste(paste("Z",2:(mb-1),sep=""),collapse="+"))) 
>
>
> n<-dim(testsamp)[1]
> testsampgroup <- rep(1,n)
> testsamp.lme <-cbind(testsamp,testsampgroup)
> testgroupSamp<- groupedData(LogY ~ WYearCen|testsampgroup, inner= ~Site,
> data= data.frame(testsamp.lme))
>
> fittest3<-lme(LogY ~ WYearCen, random= 
> pdBlocked(list(pdIdent(~-1+WYearCen:as.factor(Site)), 
> pdIdent(~-1+as.factor(Site)), pdIdent(random.model.lme))),data= 
> testgroupSamp)
> summary(fittest3)
> VarCorr(fittest3)
>
>
> # Data
>
> testsamp <-
> structure(list(Year = c(2008, 2008, 2008, 2008, 2008, 2008, 2008,
> 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2010, 2010, 2010, 2010,
> 2010, 2010, 2010, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2012,
> 2012, 2012, 2012, 2012, 2012, 2012, 2013, 2013, 2013, 2013, 2013,
> 2013, 2013, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2015, 2015,
> 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2016, 2016, 2016, 2016,
> 2016, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2018, 2018, 2018,
> 2018, 2018, 2018, 2018, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
> 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2021, 2021, 2021, 2021,
> 2021, 2021, 2021, 2022, 2022, 2022, 2022, 2022, 2022, 2022),
> WYear = c(0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 2, 2,
> 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4,
> 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7,
> 7, 7, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10,
> 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12,
> 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14, 14, 14,
> 14, 14), Site = c(4, 18, 26, 40, 67, 75, 94, 4, 18, 26, 40,
> 67, 75, 94, 4, 18, 26, 40, 67, 75, 94, 4, 18, 26, 40, 67,
> 75, 94, 4, 18, 26, 40, 67, 75, 94, 4, 18, 26, 40, 67, 75,
> 94, 4, 18, 26, 40, 67, 75, 94, 4, 18, 26, 40, 67, 75, 94,
> 4, 18, 26, 40, 67, 75, 94, 4, 18, 26, 40, 67, 75, 94, 4,
> 18, 26, 40, 67, 75, 94, 4, 18, 26, 40, 67, 75, 94, 4, 18,
> 26, 40, 67, 75, 94, 4, 18, 26, 40, 67, 75, 94, 4, 18, 26,
> 40, 67, 75, 94), LogY = c(0.848648866298552, 0.809143925760456,
> 0.734173952725014, 1.46749967704437, 0.716106254860468, 
> 0.843871512951468,
> 1.09120092433378, 0.800893809796851, 0.996674977596997, 
> 0.917613604481207,
> 1.71928772722884, 0.797853604855215, 0.922298691760041, 
> 0.964654422529188,
> 0.782903180421921, 1.13457969553106, 1.21628917384868, 2.03084776647495,
> 0.872954085910578, 1.02192794559856, 0.746307251774509, 
> 0.439812203188778,
> 1.11164109549224, 1.18414357836729, 2.00157711459358, 0.66577753155877,
> 0.856374433428581, 0.343862060001402, 0.278505653147057,
> 1.20632152691478, 1.32289150679746, 2.19814430598707, 0.538363941164496,
> 0.820038163290321, 0.070054765524828, 0.0479738684639024,
> 1.29137364087568, 1.52436357249377, 2.32150525025777, 0.595507040392793,
> 0.851417610550757, -0.115908144193410, 0.0118306018140099,
> 1.39448009350962, 1.71677754106603, 2.59146662837284, 0.595750060671620,
> 0.855387479311679, -0.430729785591898, 0.0178423104900579,
> 1.60964246000316, 1.99184029256509, 2.86865842252168, 0.695124899993409,
> 0.96175860396451, -0.600991172113926, -0.174420349224615,
> 1.73794158380868, 2.06718359946362, 3.04502112974038, 0.730730638403177,
> 0.961110819398807, -0.856693722990918, -0.549458074126028,
> 1.52302453916110, 2.05923417821491, 2.95885487422314, 0.302432275785407,
> 0.718537282886428, -1.41807557701934, -0.474811468779057,
> 1.88486023048201, 2.47921637905194, 3.31076232685622, 0.600331824659821,
> 0.997014319132077, -1.36760375228162, -0.491828047247449,
> 2.09353379020743, 2.74721582678157, 3.58818112810645, 0.65742631492698,
> 1.06027358323846, -1.58298244571648, -0.934472752299038,
> 1.83456803880667, 2.62936515021684, 3.56971226362308, 0.389323036788794,
> 0.748060984171013, -2.13928096660883, -1.26100797232926,
> 1.83430218924218, 2.65380472944419, 3.62529901196750, 0.271765247781891,
> 0.639379726021376, -2.50138714617066, -1.36434864536697,
> 1.95417376162485, 2.84537426171405, 3.76029816545047, 0.171262422338166,
> 0.63595411426061, -2.72648123827278), Y = c(2.33648781083889,
> 2.24598443402562, 2.08375999711081, 4.33837423214822, 2.04644932501053,
> 2.32535220351989, 2.97784809630864, 2.22753102803039, 2.70925849019601,
> 2.50330936997246, 5.5805521729813, 2.22076916113014, 2.51506510968675,
> 2.62388074570782, 2.18781467519546, 3.10986617752641, 3.37464176115807,
> 7.62054406285807, 2.39397241834575, 2.77854648986394, 2.10919688492552,
> 1.55241565242538, 3.03934215461328, 3.26788693363161, 7.40071868133414,
> 1.94600301201132, 2.35460841009671, 1.41038407371191, 1.32115407405314,
> 3.34117160999488, 3.75426116973332, 9.0082813655785, 1.71320166935217,
> 2.27058648893032, 1.07256691933604, 1.04914323924183, 3.63778012876121,
> 4.59222002395514, 10.1910027761430, 1.81395045797806, 2.34296591199978,
> 0.89055702237416, 1.01190086017652, 4.03287730840125, 5.56656151506009,
> 13.3493357676049, 1.81439133829339, 2.35228566604212, 0.650034535742804,
> 1.01800243542715, 5.00102284245171, 7.32900887997844, 17.6133726381587,
> 2.00395935282089, 2.61629345414488, 0.548267938797843, 0.839943753736141,
> 5.68562798048777, 7.90253504257589, 21.0104751440743, 2.07659729526341,
> 2.61459920843830, 0.424563488824068, 0.577262559146385, 4.58607500338397,
> 7.83996349588931, 19.2758857986172, 1.35314603256567, 2.05143035272921,
> 0.242179624775457, 0.622002312266844, 6.58543393476032, 11.9319106582846,
> 27.4060098478603, 1.82272352466727, 2.71017801013783, 0.254716592899401,
> 0.611507507191544, 8.11353609874542, 15.5991406590765, 36.1682306843681,
> 1.92981919064962, 2.8871607600197, 0.20536170381795, 0.392792910103641,
> 6.26242843503692, 13.8649649375266, 35.5063752059022, 1.47598127057995,
> 2.11289909722918, 0.117739471204143, 0.283368255138982, 6.26076379244682,
> 14.2079935097071, 37.5359451785784, 1.31227890476568, 1.89530490631499,
> 0.0819712136688162, 0.2555470735606, 7.0580849532232, 17.2079977586343,
> 42.961233624846, 1.18680215155599, 1.88882343537745, 0.065449185044807
> ), Z2 = c(0.47227027821606, 0.47227027821606, 0.47227027821606,
> 0.47227027821606, 0.47227027821606, 0.47227027821606, 0.47227027821606,
> 0.269868730409177, 0.269868730409177, 0.269868730409177,
> 0.269868730409177, 0.269868730409177, 0.269868730409177,
> 0.269868730409177, 0.0986058822648916, 0.0986058822648916,
> 0.0986058822648916, 0.0986058822648916, 0.0986058822648916,
> 0.0986058822648916, 0.0986058822648916, -0.0415182662167964,
> -0.0415182662167964, -0.0415182662167964, -0.0415182662167964,
> -0.0415182662167964, -0.0415182662167964, -0.0415182662167964,
> -0.150503715035887, -0.150503715035887, -0.150503715035887,
> -0.150503715035887, -0.150503715035887, -0.150503715035887,
> -0.150503715035887, -0.228350464192381, -0.228350464192381,
> -0.228350464192381, -0.228350464192381, -0.228350464192381,
> -0.228350464192381, -0.228350464192381, -0.275058513686277,
> -0.275058513686277, -0.275058513686277, -0.275058513686277,
> -0.275058513686277, -0.275058513686277, -0.275058513686277,
> -0.290627863517575, -0.290627863517575, -0.290627863517575,
> -0.290627863517575, -0.290627863517575, -0.290627863517575,
> -0.290627863517575, -0.275058513686277, -0.275058513686277,
> -0.275058513686277, -0.275058513686277, -0.275058513686277,
> -0.275058513686277, -0.275058513686277, -0.228350464192381,
> -0.228350464192381, -0.228350464192381, -0.228350464192381,
> -0.228350464192381, -0.228350464192381, -0.228350464192381,
> -0.150503715035887, -0.150503715035887, -0.150503715035887,
> -0.150503715035887, -0.150503715035887, -0.150503715035887,
> -0.150503715035887, -0.0415182662167965, -0.0415182662167965,
> -0.0415182662167965, -0.0415182662167965, -0.0415182662167965,
> -0.0415182662167965, -0.0415182662167965, 0.0986058822648916,
> 0.0986058822648916, 0.0986058822648916, 0.0986058822648916,
> 0.0986058822648916, 0.0986058822648916, 0.0986058822648916,
> 0.269868730409177, 0.269868730409177, 0.269868730409177,
> 0.269868730409177, 0.269868730409177, 0.269868730409177,
> 0.269868730409177, 0.47227027821606, 0.47227027821606, 0.47227027821606,
> 0.47227027821606, 0.47227027821606, 0.47227027821606, 0.47227027821606
> ), Z3 = c(-0.456256435177108, -0.456256435177108, -0.456256435177108,
> -0.456256435177108, -0.456256435177108, -0.456256435177108,
> -0.456256435177108, -0.0651794907395872, -0.0651794907395872,
> -0.0651794907395872, -0.0651794907395872, -0.0651794907395872,
> -0.0651794907395872, -0.0651794907395872, 0.175483244298888,
> 0.175483244298888, 0.175483244298888, 0.175483244298888,
> 0.175483244298888, 0.175483244298888, 0.175483244298888,
> 0.290800804838157, 0.290800804838157, 0.290800804838157,
> 0.290800804838157, 0.290800804838157, 0.290800804838157,
> 0.290800804838157, 0.305842225778062, 0.305842225778062,
> 0.305842225778062, 0.305842225778062, 0.305842225778062,
> 0.305842225778062, 0.305842225778062, 0.245676542018443,
> 0.245676542018443, 0.245676542018443, 0.245676542018443,
> 0.245676542018443, 0.245676542018443, 0.245676542018443,
> 0.135372788459142, 0.135372788459142, 0.135372788459142,
> 0.135372788459142, 0.135372788459142, 0.135372788459142,
> 0.135372788459142, 4.80758108354045e-17, 4.80758108354045e-17,
> 4.80758108354045e-17, 4.80758108354045e-17, 4.80758108354045e-17,
> 4.80758108354045e-17, 4.80758108354045e-17, -0.135372788459142,
> -0.135372788459142, -0.135372788459142, -0.135372788459142,
> -0.135372788459142, -0.135372788459142, -0.135372788459142,
> -0.245676542018443, -0.245676542018443, -0.245676542018443,
> -0.245676542018443, -0.245676542018443, -0.245676542018443,
> -0.245676542018443, -0.305842225778062, -0.305842225778062,
> -0.305842225778062, -0.305842225778062, -0.305842225778062,
> -0.305842225778062, -0.305842225778062, -0.290800804838157,
> -0.290800804838157, -0.290800804838157, -0.290800804838157,
> -0.290800804838157, -0.290800804838157, -0.290800804838157,
> -0.175483244298888, -0.175483244298888, -0.175483244298888,
> -0.175483244298888, -0.175483244298888, -0.175483244298888,
> -0.175483244298888, 0.0651794907395869, 0.0651794907395869,
> 0.0651794907395869, 0.0651794907395869, 0.0651794907395869,
> 0.0651794907395869, 0.0651794907395869, 0.456256435177108,
> 0.456256435177108, 0.456256435177108, 0.456256435177108,
> 0.456256435177108, 0.456256435177108, 0.456256435177108),
> Z4 = c(0.393641410895141, 0.393641410895141, 0.393641410895141,
> 0.393641410895141, 0.393641410895141, 0.393641410895141,
> 0.393641410895141, -0.168703461812203, -0.168703461812203,
> -0.168703461812203, -0.168703461812203, -0.168703461812203,
> -0.168703461812203, -0.168703461812203, -0.341732653414463,
> -0.341732653414463, -0.341732653414463, -0.341732653414463,
> -0.341732653414463, -0.341732653414463, -0.341732653414463,
> -0.276846706563615, -0.276846706563615, -0.276846706563615,
> -0.276846706563615, -0.276846706563615, -0.276846706563615,
> -0.276846706563615, -0.0979187925203697, -0.0979187925203697,
> -0.0979187925203697, -0.0979187925203697, -0.0979187925203697,
> -0.0979187925203697, -0.0979187925203697, 0.0987052888458345,
> 0.0987052888458345, 0.0987052888458345, 0.0987052888458345,
> 0.0987052888458345, 0.0987052888458345, 0.0987052888458345,
> 0.244207109056825, 0.244207109056825, 0.244207109056825,
> 0.244207109056825, 0.244207109056825, 0.244207109056825,
> 0.244207109056825, 0.297295611025701, 0.297295611025701,
> 0.297295611025701, 0.297295611025701, 0.297295611025701,
> 0.297295611025701, 0.297295611025701, 0.244207109056826,
> 0.244207109056826, 0.244207109056826, 0.244207109056826,
> 0.244207109056826, 0.244207109056826, 0.244207109056826,
> 0.0987052888458344, 0.0987052888458344, 0.0987052888458344,
> 0.0987052888458344, 0.0987052888458344, 0.0987052888458344,
> 0.0987052888458344, -0.0979187925203697, -0.0979187925203697,
> -0.0979187925203697, -0.0979187925203697, -0.0979187925203697,
> -0.0979187925203697, -0.0979187925203697, -0.276846706563615,
> -0.276846706563615, -0.276846706563615, -0.276846706563615,
> -0.276846706563615, -0.276846706563615, -0.276846706563615,
> -0.341732653414463, -0.341732653414463, -0.341732653414463,
> -0.341732653414463, -0.341732653414463, -0.341732653414463,
> -0.341732653414463, -0.168703461812203, -0.168703461812203,
> -0.168703461812203, -0.168703461812203, -0.168703461812203,
> -0.168703461812203, -0.168703461812203, 0.393641410895141,
> 0.393641410895141, 0.393641410895141, 0.393641410895141,
> 0.393641410895141, 0.393641410895141, 0.393641410895141),
> Z5 = c(-0.307723646230283, -0.307723646230283, -0.307723646230283,
> -0.307723646230283, -0.307723646230283, -0.307723646230283,
> -0.307723646230283, 0.351684167120324, 0.351684167120324,
> 0.351684167120324, 0.351684167120324, 0.351684167120324,
> 0.351684167120324, 0.351684167120324, 0.300960489170276,
> 0.300960489170276, 0.300960489170276, 0.300960489170276,
> 0.300960489170276, 0.300960489170276, 0.300960489170276,
> 0.0135263141200131, 0.0135263141200131, 0.0135263141200131,
> 0.0135263141200131, 0.0135263141200131, 0.0135263141200131,
> 0.0135263141200131, -0.230869588730213, -0.230869588730213,
> -0.230869588730213, -0.230869588730213, -0.230869588730213,
> -0.230869588730213, -0.230869588730213, -0.307416230000283,
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> 0.450234056282428, 0.450234056282428, 0.450234056282428,
> 0.450234056282428, 0.450234056282428, 0.450234056282428,
> -0.27385370433672, -0.27385370433672, -0.27385370433672,
> -0.27385370433672, -0.27385370433672, -0.27385370433672,
> -0.27385370433672, -0.15317241090017, -0.15317241090017,
> -0.15317241090017, -0.15317241090017, -0.15317241090017,
> -0.15317241090017, -0.15317241090017, 0.389893409563986,
> 0.389893409563986, 0.389893409563986, 0.389893409563986,
> 0.389893409563986, 0.389893409563986, 0.389893409563986,
> -0.153172410899934, -0.153172410899934, -0.153172410899934,
> -0.153172410899934, -0.153172410899934, -0.153172410899934,
> -0.153172410899934, -0.273853704336934, -0.273853704336934,
> -0.273853704336934, -0.273853704336934, -0.273853704336934,
> -0.273853704336934, -0.273853704336934, 0.450234056282481,
> 0.450234056282481, 0.450234056282481, 0.450234056282481,
> 0.450234056282481, 0.450234056282481, 0.450234056282481,
> -0.323223324378928, -0.323223324378928, -0.323223324378928,
> -0.323223324378928, -0.323223324378928, -0.323223324378928,
> -0.323223324378928, 0.132074282677017, 0.132074282677017,
> 0.132074282677017, 0.132074282677017, 0.132074282677017,
> 0.132074282677017, 0.132074282677017, -0.0299593420768935,
> -0.0299593420768935, -0.0299593420768935, -0.0299593420768935,
> -0.0299593420768935, -0.0299593420768935, -0.0299593420768935,
> 0.00295373795124293, 0.00295373795124293, 0.00295373795124293,
> 0.00295373795124293, 0.00295373795124293, 0.00295373795124293,
> 0.00295373795124293), Z13 = c(-0.000820388989417742, 
> -0.000820388989417742,
> -0.000820388989417742, -0.000820388989417742, -0.000820388989417742,
> -0.000820388989417742, -0.000820388989417742, 0.00984466787301128,
> 0.00984466787301128, 0.00984466787301128, 0.00984466787301128,
> 0.00984466787301128, 0.00984466787301128, 0.00984466787301128,
> -0.0533252843121323, -0.0533252843121323, -0.0533252843121323,
> -0.0533252843121323, -0.0533252843121323, -0.0533252843121323,
> -0.0533252843121323, 0.170640909798784, 0.170640909798784,
> 0.170640909798784, 0.170640909798784, 0.170640909798784,
> 0.170640909798784, 0.170640909798784, -0.351946876459913,
> -0.351946876459913, -0.351946876459913, -0.351946876459913,
> -0.351946876459913, -0.351946876459913, -0.351946876459913,
> 0.469262501946444, 0.469262501946444, 0.469262501946444,
> 0.469262501946444, 0.469262501946444, 0.469262501946444,
> 0.469262501946444, -0.351946876459763, -0.351946876459763,
> -0.351946876459763, -0.351946876459763, -0.351946876459763,
> -0.351946876459763, -0.351946876459763, 1.30897668096353e-14,
> 1.30897668096353e-14, 1.30897668096353e-14, 1.30897668096353e-14,
> 1.30897668096353e-14, 1.30897668096353e-14, 1.30897668096353e-14,
> 0.351946876459646, 0.351946876459646, 0.351946876459646,
> 0.351946876459646, 0.351946876459646, 0.351946876459646,
> 0.351946876459646, -0.469262501946203, -0.469262501946203,
> -0.469262501946203, -0.469262501946203, -0.469262501946203,
> -0.469262501946203, -0.469262501946203, 0.351946876459683,
> 0.351946876459683, 0.351946876459683, 0.351946876459683,
> 0.351946876459683, 0.351946876459683, 0.351946876459683,
> -0.170640909798657, -0.170640909798657, -0.170640909798657,
> -0.170640909798657, -0.170640909798657, -0.170640909798657,
> -0.170640909798657, 0.0533252843120879, 0.0533252843120879,
> 0.0533252843120879, 0.0533252843120879, 0.0533252843120879,
> 0.0533252843120879, 0.0533252843120879, -0.009844667873002,
> -0.009844667873002, -0.009844667873002, -0.009844667873002,
> -0.009844667873002, -0.009844667873002, -0.009844667873002,
> 0.000820388989416903, 0.000820388989416903, 0.000820388989416903,
> 0.000820388989416903, 0.000820388989416903, 0.000820388989416903,
> 0.000820388989416903), Z14 = c(0.000157883934625923, 
> 0.000157883934625923,
> 0.000157883934625923, 0.000157883934625923, 0.000157883934625923,
> 0.000157883934625923, 0.000157883934625923, -0.00221037508476475,
> -0.00221037508476475, -0.00221037508476475, -0.00221037508476475,
> -0.00221037508476475, -0.00221037508476475, -0.00221037508476475,
> 0.0143674380509829, 0.0143674380509829, 0.0143674380509829,
> 0.0143674380509829, 0.0143674380509829, 0.0143674380509829,
> 0.0143674380509829, -0.0574697522039801, -0.0574697522039801,
> -0.0574697522039801, -0.0574697522039801, -0.0574697522039801,
> -0.0574697522039801, -0.0574697522039801, 0.158041818561072,
> 0.158041818561072, 0.158041818561072, 0.158041818561072,
> 0.158041818561072, 0.158041818561072, 0.158041818561072,
> -0.316083637122359, -0.316083637122359, -0.316083637122359,
> -0.316083637122359, -0.316083637122359, -0.316083637122359,
> -0.316083637122359, 0.474125455683776, 0.474125455683776,
> 0.474125455683776, 0.474125455683776, 0.474125455683776,
> 0.474125455683776, 0.474125455683776, -0.541857663638757,
> -0.541857663638757, -0.541857663638757, -0.541857663638757,
> -0.541857663638757, -0.541857663638757, -0.541857663638757,
> 0.474125455683927, 0.474125455683927, 0.474125455683927,
> 0.474125455683927, 0.474125455683927, 0.474125455683927,
> 0.474125455683927, -0.316083637122536, -0.316083637122536,
> -0.316083637122536, -0.316083637122536, -0.316083637122536,
> -0.316083637122536, -0.316083637122536, 0.158041818561182,
> 0.158041818561182, 0.158041818561182, 0.158041818561182,
> 0.158041818561182, 0.158041818561182, 0.158041818561182,
> -0.0574697522040225, -0.0574697522040225, -0.0574697522040225,
> -0.0574697522040225, -0.0574697522040225, -0.0574697522040225,
> -0.0574697522040225, 0.0143674380509932, 0.0143674380509932,
> 0.0143674380509932, 0.0143674380509932, 0.0143674380509932,
> 0.0143674380509932, 0.0143674380509932, -0.00221037508476627,
> -0.00221037508476627, -0.00221037508476627, -0.00221037508476627,
> -0.00221037508476627, -0.00221037508476627, -0.00221037508476627,
> 0.00015788393462604, 0.00015788393462604, 0.00015788393462604,
> 0.00015788393462604, 0.00015788393462604, 0.00015788393462604,
> 0.00015788393462604), WYearCen = c(-7, -7, -7, -7, -7, -7,
> -7, -6, -6, -6, -6, -6, -6, -6, -5, -5, -5, -5, -5, -5, -5,
> -4, -4, -4, -4, -4, -4, -4, -3, -3, -3, -3, -3, -3, -3, -2,
> -2, -2, -2, -2, -2, -2, -1, -1, -1, -1, -1, -1, -1, 0, 0,
> 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2,
> 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5,
> 5, 5, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7)), .Names = c("Year",
> "WYear", "Site", "LogY", "Y", "Z2", "Z3", "Z4", "Z5", "Z6", "Z7",
> "Z8", "Z9", "Z10", "Z11", "Z12", "Z13", "Z14", "WYearCen"), row.names 
> = c(4L,
> 18L, 26L, 40L, 67L, 75L, 94L, 104L, 118L, 126L, 140L, 167L, 175L,
> 194L, 204L, 218L, 226L, 240L, 267L, 275L, 294L, 304L, 318L, 326L,
> 340L, 367L, 375L, 394L, 404L, 418L, 426L, 440L, 467L, 475L, 494L,
> 504L, 518L, 526L, 540L, 567L, 575L, 594L, 604L, 618L, 626L, 640L,
> 667L, 675L, 694L, 704L, 718L, 726L, 740L, 767L, 775L, 794L, 804L,
> 818L, 826L, 840L, 867L, 875L, 894L, 904L, 918L, 926L, 940L, 967L,
> 975L, 994L, 1004L, 1018L, 1026L, 1040L, 1067L, 1075L, 1094L,
> 1104L, 1118L, 1126L, 1140L, 1167L, 1175L, 1194L, 1204L, 1218L,
> 1226L, 1240L, 1267L, 1275L, 1294L, 1304L, 1318L, 1326L, 1340L,
> 1367L, 1375L, 1394L, 1404L, 1418L, 1426L, 1440L, 1467L, 1475L,
> 1494L), class = "data.frame")
>
>
>
>
>
>
> At 11:17 AM 5/22/2009 -0700, spencerg wrote:
>> The first exaample on the "lmer" help page uses a formula "Reaction ~ 
>> Days + (Days|Subject)". Here, "Subject" is the name of a column in 
>> the data.frame "sleepstudy", with levels "308", "309", ... .
>>
>> Does this answer your question? If no, please provide commented, 
>> minimal, self-contained, reproducible code, as requested in the 
>> posting guide "http://www.R-project.org/posting-guide.html". Your 
>> example is not "self-contained, reproducible".
>>
>> Hope this helps. Spencer
>>
>>
>> Leigh Ann Starcevich wrote:
>>> Dear guRus:
>>>
>>> I am using lmer for a mixed model that includes a random intercept 
>>> for a set of effects that have the same distribution, Normal(0, 
>>> sig2b). This set of effects is of variable size, so I am using an 
>>> as.formula statement to create the formula for lmer. For example, if 
>>> the set of random effects has dimension 8, then the lmer call is:
>>>
>>> Zs<- paste("Z",1:mb,sep="")
>>> Trendformula <-as.formula(paste("LogY ~ WYear + (1+WYear|Site) + 
>>> (1|", paste(paste(Zs,collapse="+"), ")")))
>>> fit2.4a<-lmer(Trendformula, data = testsamp)
>>>
>>> which, for mb=8, expands to:
>>>
>>> fit1<-lmer(LogY ~ WYear + (1 | Site) + (1 | Year) + (1 | Z1+ Z2 + Z3 
>>> + Z4 + Z5 + Z6 + Z7 + Z8), data = testsamp)
>>>
>>>
>>> I have no problems with this. However, if the set of random effects 
>>> has a dimension of 30, then the lmer call is:
>>>
>>> fit2<-lmer(LogY ~ WYear + (1 | Site) + (1 | Year) + (1 | Z1+Z2 + Z3 
>>> + Z4 + Z5 + Z6 + Z7 + Z8 + Z9 + Z10 + Z11 + Z12 + Z13 + Z14 + Z15 + 
>>> Z16 + Z17 + Z18 + Z19 + Z20 + Z21 + Z22 + Z23 + Z24 + Z25 + Z26 + 
>>> Z27 + Z28 + Z29+ Z30), data = testsamp)
>>>
>>> In this case, I get an error because the name "Z1+Z2 + Z3 + Z4 + Z5 
>>> + Z6 + Z7 + Z8 + Z9 + Z10 + Z11 + Z12 + Z13 + Z14 + Z15 + Z16 + Z17 
>>> + Z18 + Z19 + Z20 + Z21 + Z22 + Z23 + Z24 + Z25 + Z26 + Z27 + Z28 + 
>>> Z29+ Z30" is too long to print in the output. Is there any way to 
>>> name the random effect in lmer so that the shorter (and more 
>>> descriptive) name may be used and the error avoided? Or is there a 
>>> way to combine these into a single variable prior to the lmer 
>>> function call? In SAS, I am able to parameterize these as a Toeplitz 
>>> structure with bandwidth 1.
>>>
>>> Thanks for any help.
>>>
>>> Leigh Ann Starcevich
>>> Doctoral student
>>> Oregon State University
>>> Corvallis, Oregon
>>> [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
>>> R-help at 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.
>>>
>>>
>>
>