similar to: more documentation on lmer?

Displaying 20 results from an estimated 1000 matches similar to: "more documentation on lmer?"

2004 Apr 26
2
mixed model with binomial link?
Hello. I have to fit a mixed model from a repeated measures split-plot experiment in which the response variable is binary. This requires a generalised linear mixed model in which I can specify a binomial distribution. I can’t find the appropriate package in R. I have looked at glmmML, but it doesn’t seem to allow any mixed structure beyond a simple 2-level one. Can anyone point me to the
2004 Sep 30
1
histograms with more than one variable
Hello. I want to plot the distribution of a continuous variable (y) in each of two groups on the same graph as histograms. I suppose one could call this a 2-d histogram? Can this be done in R? Here is a typical data.set: y group 1.2 1 3.3 1 2.4 2 5.7 1 0.2 2 etc. Bill Shipley Subject Matter Editor, Ecology North American Editor, Annals of
2004 Oct 04
3
(off topic) article on advantages/disadvantages of types of SS?
Hello. Please excuse this off-topic request, but I know that the question has been debated in summary form on this list a number of times. I would find a paper that lays out the advantages and disadvantages of using different types of SS in the context of unbalanced data in ANOVA, regression and ANCOVA, especially including the use of different types of contrasts and the meaning of the
2003 Oct 28
1
setting up complicated ANOVA in R
Hello. I am about to do a rather complicated analysis and am not sure how to do it. The experiment has a split-plot design and also repeated measures. Both of these complications require one to define an error term and it seems that one cannot specify two such terms. The split-plot command is: aov(y~covariates +A*B+Error(C), data=) where A and B are the fixed effects and C is the
2003 Dec 11
2
typeIII SS for lme?
To avoid angry replies, let me first say that I know that the use of Type III sums of squares is controversial, and that some statisticians recommend instead that significance be judged using the non-marginal terms in the ANOVA. However, given that type III SS is also demanded by some… is there a function (equivalent to drop1 for lm) to obtain type III sums of squares for mixed models using the
2004 Apr 01
1
nls function
Hello. I am trying to fit a non-rectangular hyperbola function to data of photosynthetic rate vs. light intensity. There are 4 parameters that have to be estimated. I find the nls function very difficult to use because it often fails to converge and then gives out cryptic error messages. I have tried playing with the control parameters but this does not always help. Is there another
2005 Jan 05
1
cubic spline smoother with heterogeneous variance.
Hello. I want to estimate the predicted values and standard errors of Y=f(t) and its first derivative at each unique value of t using the smooth.spline function. However, the data (plant growth as a function of time) show substantial heterogeneity of variance since the variance of plant mass increases over time. What is the consequence of such heterogeneity of variance in terms of bias in the
2005 Feb 15
1
shrinkage estimates in lme
Hello. Slope estimates in lme are shrinkage estimates which pull the OLS slope estimates towards the population estimates, the degree of which depends on the group sample size and the distance between the group-based estimate and the overall population estimate. Although these shrinkage estimates as said to be more precise with respect to the true values, they are also biased. So there is a
2004 Oct 01
3
controlling colour in Trellis histogram
Hello. I am sorry for posting a (seemingly) simple question, but I have just spent 2 hours trying to find the answer, without success. I want to make a histogram with conditioning on a factor, using Trellis graphics. However, I do not want any colours (only black and white) either in the histograms or in the strip. There must be some simple argument but I can’t find it. Here is my code so
2006 Apr 13
1
obtaining residuals from lmer
Hello. I cannot find out how to extract the residuals from a mixed model using the lmer function. Can someone help? Bill Shipley North American Editor, Annals of Botany Editor, "Population and Community Biology" series, Springer Publishing Département de biologie, Université de Sherbrooke, Sherbrooke (Québec) J1K 2R1 CANADA Bill.Shipley@USherbrooke.ca
2003 Nov 25
1
using pdMAT in the lme function?
Hello. I want to specify a diagonal structure for the covariance matrix of random effects in the lme() function. Here is the call before I specify a diagonal structure: > fit2<-lme(Ln.rgr~I(Ln.nar-log(0.0011)),data=meta.analysis, + random=~1+I(Ln.nar-log(0.0011)|STUDY.CODE,na.action=na.omit) and this works fine. Now, I want to fix the covariance between the between-groups slopes
2004 Feb 19
1
controlling nls errors
Hello. I am using the nonlinear least squares function (nls). The function that I am trying to fit seems to be very sensitive to the starting values and, if these are not chosen properly, the nls function stops and gives an error message: Error in numericDeriv(form[[3]], names(ind), env) : Missing value or an Infinity produced when evaluating the model In addition: Warning
2003 Nov 04
3
help with lme()
Hello. I am trying to determine whether I should be using ML or REML methods to estimate a linear mixed model. In the book by Pinheiro & Bates (Mixed-effects models in S and S-PLUS, page 76) they state that one difference between REML and ML is that « LME models with different fixed-effects structures fit using REML cannot be compared on the basis of their restricted likelihoods. In
2006 Feb 16
1
help downloading lme4 from CRAN
Hello. I am having trouble downloading the lme4 package from the CRAN site. The error is: > local({a <- CRAN.packages() + install.packages(select.list(a[,1],,TRUE), .libPaths()[1], available=a, dependencies=TRUE)}) trying URL `http://cran.r-project.org/bin/windows/contrib/2.0/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 26129 bytes opened URL downloaded 25Kb
2003 Oct 31
1
help with constrOptim function
Hello. I had previously posted a question concerning the optimization of a nonlinear function conditional on equality constraints. I was pointed towards the contrOptim function. However, I do not understand the syntax of this function with respect to specifying the constraints and so I don’t know if it is what I need. The command is: constrOptim(theta, f, grad,ui,ci,…). “theta” is the
2004 Jul 16
1
specifying a function in nls
Hello. I am trying to understand the syntax of the nonlinear least squares function (nls) when the function definition is made outside of the call. Here is the context. 1. If I specify the following command, it works fine: > fit2<-nls( + A~Am*(1-exp(-alpha*(I-LCP))),data=dat1, + start=list(Am=3.6,alpha=0.01,LCP=20)) 2. Now, I want to be able to specify the function definition
2006 Jun 01
1
help with syntax of nlme function
I am having difficulty understanding the syntax of the nlme() function for nonlinear mixed models. The data frame is called Marouane.chlorophyll. The model involves a dependent variable (Absorb) and an independent variable (Ch.surf), which are both numeric variables in the data frame. The data are hierarchically grouped as Espece, Plante nested within Espece, and Feuille nested within Plante
2003 Oct 21
3
explaining curious result of aov
Hello. I have come across a curious result that I cannot explain. Hopefully, someone can explain this. I am doing a 1-way ANOVA with 6 groups (example: summary(aov(y~A)) with A having 6 levels). I get an F of 0.899 with 5 and 15 df (p=0.51). I then do the same analysis but using data only corresponding to groups 5 and 6. This is, of course, equivalent to a t-test. I now get an F of 142.3
2003 Oct 31
1
constrained nonlinear optimisation in R?
Hello. I have searched the archives but have not found anything. I need to solve a constrained optimisation problem for a nonlinear function (“maximum entropy formalism”). Specifically, Optimise: -1*SUM(p_ilog(p_i)) for a vector p_i of probabilities, conditional on a series of constraints of the form: SUM(T_i*p_i)=k_i for given values of T_i and k_i (these are constraints on
2003 Oct 21
0
summary of "explaining curious results of aov"
Earlier, I had posted the following question to the group : > Hello. I have come across a curious result that I cannot explain. > Hopefully, someone can explain this. I am doing a 1-way ANOVA with 6 > groups (example: summary(aov(y~A)) with A having 6 levels). I get an > F of 0.899 with 5 and 15 df (p=0.51). I then do the same analysis but > using data only