similar to: using lme4 with three nested random effects

Sub: using glmer to fit a mixed-effects model with gamma-distributed response variable Hello, I'm currently trying to fit a mixed effects model , i.e.: > burnedmodel1.2<-glmer(gpost.f.crwn.length~lg.shigo.av+dbh+leaf.area+ bark.thick.bh+ht.any+ht.alive+(1|site/transect/plot), family=gaussian, na.action=na.omit, data=rws30.BL) If I run this code, I get the error below: Error:

Apologies for continuing to ask about this but . . in my quest to fit a gamma GLMM model to my data (see partial copy of thread below), I'm exploring using hglm today. The question of the day has to do with the errors I'm currently getting from the hglm package. Can hglm handle a model with nested random effects? I don't see an example of one of those in the package documentation. If

Addendum: I tried a gamma fit in glmmPQL and got the same errors. *Ben Caldwell* PhD Candidate University of California, Berkeley On Tue, May 17, 2011 at 3:51 PM, Benjamin Caldwell <btcaldwell@berkeley.edu>wrote: > Hello > After seeing this ( > https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q1/005213.html) email > I thought I would check the issue with a gamma family

Hello, I'm trying to compare the fit of two distributions, normal and gamma, to a histogram of my response variable. rate<-mean(na.omit(rwb$post.f.crwn.length))/var(na.omit(rwb$post.f.crwn.length)) shape<-rate*mean(na.omit(rwb$post.f.crwn.length)) hist((rwb$post.f.crwn.length), main="rwb$post.f.crwn.length")

Hi folks, I'm dealing with a dataset with a lot of NAs, and want to use subset on the data without removing the NAs from the the dataframe; e.g. rws50 <- subset(rw.fire.RW,shigo.av<50) This removes instances with NA for the value in addition to anything <50. Any suggestions much appreciated. *Ben Caldwell* [[alternative HTML version deleted]]

I'm trying out a basic plot, but something about the way I subset my data leads to problems with the plot. Here is the first bit of my data set year,date,location,quadrat_juvenile,photo_location,photo_exists,genus,count,divers 2005,2005-04-30, 1 Fringing Reef,1, 1 Fringing Reef Coral Transect Pole 1-2 Quadrat 1,t,Acanthastrea,0,HP+MEM 2005,2005-04-30, 1 Fringing Reef,1, 1 Fringing Reef

Dear All, I would like to make partial sums (or means or any other function) of the values in intervals along a sequence (spatial transect) where groups are defined. For instance: habitats<-rep(c("meadow","forest","meadow","pasture"),c(10,5,12,6)) observations<-rpois(length(habitats),2)

R-help readers, I''m having a problem with an R script (see below), which regularly generates the error message, Error in start:(start + (sample.length - 1)) : NA/NaN argument , for which I am unsure of the cause. In essence, the script (below) generates the start and end points for random subsamples from along a vector (in reality a transect (of a given length,

Dear R friends, I have a matrix with 2060 rows and 41 columns. One column is Date, another is Transect, and another is Segment. I want to ensure that there are 9 Transects (1 to 9) for each Date, and 8 Segments (1 to 8) for each Transect in the matrix, by inserting rows where these are missing. I am new to coding, but am trying to write a loop which checks if each of the transects already

Hi all, I'm trying to run a repeated measures ANOVA on some univariate ecological data that was collected over two growing seasons. I ran the test using the methodology found on this website: http://rtutorialseries.blogspot.com/2011/02/r-tutorial-series-one-way-repeated.html Upon running the actual ANOVA I got this error message: "> rmanova=anova(yearmodel, idata=yearframe,

I have data on number of vines per tree for ~550 trees. Over half of the trees did not have any vines and the data is fairly skewed (median = 0, mean = 1.158, 3rd qu. = 1.000). I am attempting to investigate whether plot location (four sites), species (I'm using only the four most common species), or tree dbh has a significant influence on the number of vines per tree. When I

Hello everybody, In am trying to analyse a BACI experiment and I really want to do it with R (which I find really exciting). So, before moving on I though it would be a good idea to repeat some known experiments which are quite similar to my own. I tried to reproduce 2 published examples but without much success. The first one in particular is a published dataset analysed with SAS by

Dear R gurus, I have XY data giving the locations of tree seedlings that were surveyed during a 210 meter belt transect. This belt transect was taken by stretching a line across the field, then measuring all seedlings within 1 meter on either side of the line. The end result was XY coordinates and height for ~1,300 seedlings. I would like to use that data to calculate density of

Hi, I wonder if someone can help me. I have built a gam model to predict the presence of cold water corals and am now trying to evaluate my model by splitting my dataset into training/test datasets. In an ideal world I would use the sample() function to randomly select rows of data for me so for example with 936 rows of data in my HH dataset I might say ss <- sample(nrow(HH), size =

Hi, I'm trying to analyse some data I have imported into R from a .csv file but when I carry out the aov command the results show only one degree of freedom when there should be 14. Does anyone know why? I'd really appreciate some help, the data is pasted below. /The imported table looks ike this this:/ Order Transect Sample Abundance 1 Coleoptera 1 1 13 2

Hi, I have a question about computing shortest Euclidean distances between two data frames of spatial points... I have 2 dataframes (not yet converted to spatial class) >Sewers<-data.frame(x=c(10,20,35,50),y=c(100,150,200,300)) >transect <- data.frame(x=seq(from=0, to=50, by=1),y=seq(from=100, to=150, by=1)) I would like to be able to compute the shortest distance from the

Hi again. Perhaps a simple question this time.... I am analysing data with a dependent variable of insect counts, a fixed effect of site and two random effects, day, which is the same set of 10 days for each site, and then transect, which is nested within site (5 each). I am trying to fit the cross classified model using GLMM in lme4. I have, for potential use, created a second coding

Hi all, I'm modeling using lme in the nlme package. qqnorm makes plots just find, but when I try to add a line with qqline, I get the following error: "Error in sort.list(x, partial = unique(c(lo, hi))) : 'x' must be atomic for 'sort.list' Have you called 'sort' on a list?" For example > modelincr10<-lme(lruin~can.pos.num, data=rwushi30, random=(~1|

Hello, I have the following loop for two data sets: diveData_2008 and diveData_2009. It uses two other data: diveCond_all and fishTable. The problem is at the point to identify the dive_id for the given index (index is timestamp). It keeps on saying for the1st loop Error in fishReport$dive_id[i] <- dive_id : replacement has length zero for the 2nd loop Error in fishReport$dive_id[i + j] <-

Hi list members. I’ll try to plot the abundance means of nine transects as lines, with five points on each transect (A to I). I will also need to plot for each point, it’s standard deviation (once each point will have tree replicates) as whiskers. Another problem will be that all the points should exist for each transect, but we know that six of the nine transects will have blanks (A1, A2, A3, -,