similar to: linear model lme4

Dear R users I have built several glmm models using glmmPQL in the following structure: m1<-glmmPQL(dev~env*har*treat+dens, random = ~1|pop/rep, family = Gamma) (full script below, data attached) I have tried all the methods I can find to obtain some sort of model fit score or to compare between models using following the deletion of terms (i.e. AIC, logLik, anova.lme(m1,m2)), but I

Dear all R-users, When I install the package "lme4" in R-2.11.1, and use it to run the simulation on the Linux system, it appears the following problem. Attaching package: 'lme4' The following object(s) are masked from 'package:stats':     AIC Error in names(argNew)[1] <- names(formals(new))[[1]] :   replacement has length zero Calls: initial ... lmerFactorList

Dear all, I want to estimate a crossed-random-effects model (i.e., measurements, students, schools) where students migrate between schools over time. I'm interested in the fixed effects of "SES", "age" and their interaction on "read" (reading achievement) while accounting for the sample design. Based on a previous post, I'm specifying my model as: fm1 <-

Hi, Sorry for a basic questions on linear models. I am trying to adjust raw data for both fixed and mixed effects. The data that I output should account for these effects, so that I can use the adjusted data for further analysis. For example, if I have the blood sugar levels for 30 patients, and I know that 'weight' is a fixed effect and that 'height' is a random effect, what

Dear Group, I am having a function that I am running in a loop that generated two results for each loop The result1 is a zoo object The result2 is a data frame Now I want to put both of them in a list or some structure ... that I can access or output to a file after the loop is done. For e.g. for (i in 1:20){ niceFunction(x[i],i) } niceFunction (x,i) { result1 = someOperations() #zoo

Dear List, Shouldn't result1 and result2 be equal in the following case? Note that log$RequestID is a factor. That is, is.factor(log$RequestID) yields TRUE. result1 <- tapply(log$Flag,factor(log$RequestID),sum) result2 <- tapply(log$Flag,log$RequestID,sum) Yet, when I summarize the output, I get the following: summary(result1) Min. 1st Qu. Median Mean 3rd Qu.

Hopefully an easy one, how do I merge two or more SQL query results? Example: result1 = find_by_sql(x) result2 = find_by_sql(y) What is the best way to merge result1 and result2? I want to be able to reference the objects as if they were obtained via one query. Cheers, Dan

Hello everyone, What is the most efficient & simpliest way to convert all components of a list to separate columns in a matrix? Is there an easy way to programmatically "pad" the length of the resulting shorter character vectors so that they can be easily combined into a data frame? I have the following code that stores the 2 compoents (of differing lengths) in the same character

Thank you for your help in advance. I am trying to pull some data back from a web service library(httr) sample2 <- GET("https://elevation.mapzen.com/height?json={\"range\":false,\"shape\":[{\"lat\":40.7,\"lon\":-76.5}]}&api_key=mycode") result2 <- content(sample2) height <- result2$height[[1]] I would like to put by own latitude

Hi, I was wondering: I've got a dataset where I've got student 'project's nested within 'school's, and 'division' (elementary, junior, or senior) at the student project level. (Division is at the student level and not nested within schools because some students are registered as juniors & others as seniors within the same school.) So schools are random,

On Sep 24, 2013, at 4:07 PM, Sean Silva <chisophugis at gmail.com> wrote: > On Tue, Sep 24, 2013 at 4:17 PM, Nick Kledzik <kledzik at apple.com> wrote: > > On Sep 24, 2013, at 12:40 PM, Michael Spencer <bigcheesegs at gmail.com> wrote: > >> On Tue, Sep 24, 2013 at 12:33 PM, Rui Ueyama <ruiu at google.com> wrote: >> Hi LLD developers, >>

On Tue, Sep 24, 2013 at 4:17 PM, Nick Kledzik <kledzik at apple.com> wrote: > > On Sep 24, 2013, at 12:40 PM, Michael Spencer <bigcheesegs at gmail.com> > wrote: > > On Tue, Sep 24, 2013 at 12:33 PM, Rui Ueyama <ruiu at google.com> wrote: > >> Hi LLD developers, >> >> I'm about to make a change to invert the return value of Driver::parse()

Dear All, The following code extracts from NCBI very nice output for ONE allele of a SNP (often the allele with the second largest frequency - usually termed the minor allele). It gives an average minor allele frequency from all NCBI sources (which is what I want, except I'd like the addition of data for all the other alleles of one SNP) plus a table of minor allele frequencies from each

I've seen some questions regarding the output of multiple objects from a function, however the suggestions all end up suggesting the use of return(list(result1=result1, result2=result2 , result3=result3)). How can I return multiple objects that are 2 big to be added to a list? -- View this message in context:

On Tue, Sep 24, 2013 at 4:44 PM, Nick Kledzik <kledzik at apple.com> wrote: > > On Sep 24, 2013, at 4:07 PM, Sean Silva <chisophugis at gmail.com> wrote: > > On Tue, Sep 24, 2013 at 4:17 PM, Nick Kledzik <kledzik at apple.com> wrote: > >> >> On Sep 24, 2013, at 12:40 PM, Michael Spencer <bigcheesegs at gmail.com> >> wrote: >> >>

a) you need to read the help pages on the paste function... more likely you are looking for the paste0 function because extra spaces will most likely break the GET request format. b) quotes do not become "stuck" as \" ... that is a visual representation intended to clarify that that quote is not terminating the string but is actually part of it. If you want to see the contents

Hi, I am using lmer (from the package lme4) to predict a binary response variable (REL) from a bunch of fixed effects and two random effects (Speaker_ID and NPhead_lemma): fit <- lmer(REL ~ SPEAKER_GENDER + log(SPEECHRATE) + SQSPEECHRATE + ..... + (1|Speaker_ID) + (1|NPhead_lemma), family="binomial", data=data.lmer, method="Laplace", model=T, x=T) I

Hi, I ran the following model using nlme: model2<-lme(log(malrat1)~I(year-1982),random=~1|Continent/Country,data=wbmal10) I'm trying to run a Poisson GlMM to avoid the above transformation but I don't know how to specify the model using lmer in the lme4 library: model3<-lmer((malrat1)~I(year-1982) + ??,data=wbmal10,family=poisson) How can I introduce a random factor of the

Dear all, I have three concerns: 1) I am running models with the lme4 package. I cannot find a way to pull out a vector of the fitted values and the residuals. Does anybody know how to do it? 2) How can I nest a random effect variable into a "two-level" fixed effect variable? 3) Suppose I have the following model: y = a + b|c + d + error, where 'a' is a fixed effect, 'c'

I suspect the weights argument is not having any effect. Package: Matrix Version: 0.995-2 Date: 2006-01-19 Beginning with this: Browse[1]> resp.lmer <- lmer(SensSSC ~ Block + Season + (1 | Plot) + (1 | Ma) + (1 | Pa) + + (1 | MaPa), weights = SensSSC.N, data = xx) I group the output into a table with my ran.eff function and get this: