similar to: nls vs nlme: parameter constraints

Dear Thomas Lumley, and R-help list members, I have read your article "Network meta-analysis for indirect treatment comparisons" (Statist Med, 2002) with great interest. I found it very helpful that you included the R code to replicate your analysis; however, I have had a problem replicating your example and wondered if you are able to give me a hint. When I use the code from the

My question concerns the logic behind hypothesis tests for fixed-effect terms in models fitted with lme. Suppose the levels of Subj indicate a grouping structure (k subjects) and Trt is a two-level factor (two treatments) for which there are several (n) responses y from each treatment and subject combination. If one suspects a subject by treatment interaction, either of the following models seem

I have three columns of data, Xc, Trt and fish. This was a repeated measures design with 6 measurements taken from each of 5 fish. Xc is the actual measurement, Trt is the treatment, and fish is the fish number. Data can be seen below (hopefully it is in the column format). I would like to look for differences between treatments in a repeated measures format. I used the following code

Hi, I asked this on mixed model mailing list, but that list is not very active, so I'd like to try the general R mailing list. Sorry if anyone receives the double post. Hi, I have a dataset of animals receiving some eye treatments. There are 8 treatments, each animal's right and left eye was measured with some scores (ranging from 0 to 7) 4 times after treatment. So there are

Dear r-helpers, Spencer Graves and Manual Morales proposed the following methods to simulate p-values in lme4: ************preliminary************ require(lme4) require(MASS) summary(glm(y ~ lbase*trt + lage + V4, family = poisson, data = epil), cor = FALSE) epil2 <- epil[epil$period == 1, ] epil2["period"] <- rep(0, 59); epil2["y"] <- epil2["base"]

Hi al, I have a dataset (see attached), which basically involves 4 treatments for a chemotherapy drug. Samples were taken from 2 biopsy locations, and biopsy were taken at 2 time points. So each subject has 4 data points (from 2 biopsy locations and 2 time points). The objective is to study treatment difference.? I used lme to fit a mixed model that uses "biopsy.site nested within pid"

Hello, I am trying to run a mixed effects nested ANOVA but none of my codes are giving me any meaningful results and I am not sure what I am doing wrong. I am a new user on R and would appreciate some help. The experimental design is that I have some frogs that have been exposed to three acoustic Treatments and I am measuring neural activity (egr), in 12 brain regions. Some frogs also called

Dear friends - I'm having troubles with nlme fitting a simplified model as shown below eliciting the error Error in chol.default((value + t(value))/2) : ? the leading minor of order 1 is not positive definite - I have seen the threads on this error but it didn't help me solve the problem. The model runs well in brms and identifies the used parameters even with fixed effects for TRT?

Dear R - Users I have some problems fitting a linear mixed effects model using the lme function (nlme library). A sample data is as shown at the bottom of this mail. I fit my linear mixed model using the following R code: bmr <-lme (outcome~ -1 + as.factor(endpoint)+ as.factor(endpoint):trt, data=datt, random=~-1 + as.factor(endpoint) + as.factor(endpoint):trt|as.factor(Trial),

I use model comparison with glms without mixed effects with anova(modelA,modelB), with mixed effects glm (glmmPQL), this doesn't work. Is there a way to compare model fits with glmmPQL's? Paula M. den Hartog Behavioural Biology Institute of Biology Leiden Leiden University [[alternative HTML version deleted]]

Hello, I've been fitting a random effects model using nlme to some data, but I am discovering that the variation in my random effect is very small. As a result, I would like to replace it as a fixed effect (i.e. essentially fit the same model but with no random effect). As I understand it I could do this using nls(), but I'm using a number of options such as weights = varPower()

Let's say I have the following string: str <- "P = 0.0, T = 0.0, Q = 0.0" I'd like to find a function that generates the following object from 'str'. list(P = 0.0, T = 0.0, Q = 0.0) Thanks! -- http://mutualism.williams.edu

Dear R users, I'm hoping that more experienced users will be able to assist me in examining the model fit of a mixed generalised linear model. The example using the data 'bacteria' within the MASS package will hopefully illustrate what I would like to acheive; library(MASS) library(nlme) attach(bacteria) # y being output and the trt - treatment group being an explanatory variable.

hi, is there an option to calculate the 'within' & 'between' group variances for a simple ANOVA (aov) model (2 groups, 1 trait, normally distr.) ? or do I have to calculate them from the Sum Sq ? thanks for your time and greetings, gregor -- Gregor Rolshausen PhD Student; University of Freiburg, Germany e-mail: gregor.rolshausen at biologie.uni-freiburg.de tel. :

I have been using lme from nlme to do a 3-way anova with all the effects treated as random. I was wondering if someone could direct me to an example of how to do this using lmer from lme4. I have 3 main effects, tim, trt, ctr, and all the interaction effects tim*trt*ctr. The response variable is ge. Here is my lme code: dat <-

Hallo, I have a question that is more statistic related than about nlme and R functioning. I want to fit a complicated nonlinear model with nlme with several different measures of transpiration taken on each of the 220 trees grouped in 8 families. The unknown parameters of the model are three + their variances (and covariances). I want to estimate the variances among families of the

Dear, I have a dataset with 4 subjects (see ID in example), and 4 treatment (see TRT in example) which are tested on 2 locations and in 3 blocs. By using Lattice dotplot, I made a graph that shows the raw data per location and per bloc. In that graph, I would like to have a reference line per bloc that refers to the first treatment (T1). However, I can not find how to do that. I can make

Dear Madam or Sir, I need to do multiple comparisons following nlme analysis (Compare the effects of different treatments on a response measured repeatedly over time; fixed = response ~ treat*time). On the web I found the notion that one might use the L argument from ANOVA. Do you have an example to show how this works together with nlme? Are there other ways to do a post-hoc analysis in

Hi I am running some linear and non-linear mixed effect models and would like to do some planned contrasts (a priori contrasts) I have looked in the help and in many forums and it seems possible to do so but don't understand how to write the function and I couldn't find an example in Pinheiro and Bates. lme {nlme} has a contrasts argument but I can't understand how to code it.

Hi there, The following data is obtained from a long-term experiments. > mydata <- read.table(textConnection(" + y year Trt + 9.37 1993 A + 8.21 1995 A + 8.11 1999 A + 7.22 2007 A + 7.81 2010 A + 10.85 1993 B + 12.83 1995 B + 13.21 1999 B + 13.70 2007 B + 15.15 2010 B + 5.69 1993 C + 5.76 1995 C + 6.39 1999