search for: nlmer

I am trying to explore nlmer by running some nlme examples from Pinheiro & Bates (2000). I do not seem to find information how to specify fixed effects covariates to nlmer models. Specifically, I tried to run the "Carbon Dioxide Uptake" example from p. 368 onwards in the PB200 book. The model without fixed effect...

Hi, I have R 2.6.0 with updated lme4 and Matrix packages, and I am trying to fit a nonlinear multilevel model. I get the following error message: Error in nlmer(f ~ grModel(x, w, Tmin, Tmax, Topt, kopt, m) ~ kopt | flat, : gradient attribute of evaluated model must be a numeric matrix and I wonder what this may indicate. The nonlinear model I try to fit is as follows: > grModel function(x,w,Tmin,Tmax,Topt,kopt,m)((x-Tmin)*(x-Tmax))/((x-Tmin)*(x-T...

...some horizontal asymptote, and increases unboundedly as time passes) There is one grouping variable (let's call it "ID"). Most of the fixed effects need to have a random component, i.e. for different ID's they would vary around the fixed mean. Here are my questions: 1. Do nlme/nlmer accept on the RHS of the main formula, only SelfStart-type objects? (I assume yes, because I tried to code the RHS directly in the formula with no success). 2. If so, is there any SelfStart object I can take "off the shelf" and use for this - or must I create my own? (would need guidance...

...ovariates (temperature and time). The response to temperature is modeled by a kind of beta function with 2 parameters (optimal and maximum temperatures) and the time function is a 2-parameter Weibull. Adjustments with nls or gnls work, but I need to do mixed-effects modeling. It seems like nlme or nlmer need self starting functions, but so far I can't find a way to code a selfstart function with 2 "x" covariates. Is it just impossible? Is there another way? Thanks -- View this message in context: http://r.789695.n4.nabble.com/Custom-nonlinear-self-starting-function-w-2-covariates-t...

I found this by accident yesterday. The program that crashes is the first two lines of the example from the help page for nlmer. That example hasn't changed in a long time, so I assumed that it is an R-devel issue. It could also be a long latent nlmer bug. The second run with valgrind is puzzling. Terry T. > library(lmer) > sessionInfo() R Under development (unstable) (2017-02-21 r72241) Platform: i686-pc-...

...to https://github.com/lme4/lme4/issues/412 for further discussion ... On Wed, Feb 22, 2017 at 10:03 AM, Therneau, Terry M., Ph.D. <therneau at mayo.edu> wrote: > I found this by accident yesterday. The program that crashes is the first > two lines of the example from the help page for nlmer. That example hasn't > changed in a long time, so I assumed that it is an R-devel issue. It could > also be a long latent nlmer bug. The second run with valgrind is puzzling. > > Terry T. > > >> library(lmer) >> sessionInfo() > R Under development (unstable) (2...

...dure is repeated weekly on each individual (MRN), so each individual has 5-9 cases associated with them. Currently I am including these in the model as if they were independent. Is there a way to account for the non-independence of these waking times? I'm thinking of something similar to the NLMER package and Multilevel / Mixed Effects analysis as described in Pinheiro and Bates. I'd be appreciative of any help at all? Thanks again, R -- View this message in context: http://r.789695.n4.nabble.com/Multilevel-Survival-Analysis-Cox-PH-Model-tp3638278p3638278.html Sent from the R help m...

Hi all, after browsing the archives for hours I'm still not sure about the proper analysis for my dataset. I subjected each of about 50 critters (about 10 each in 5 distinct populations) to 4 consecutive treatments (exposure to increasing concentrations), with one measurement per treatment and individual. I, of course, want to know, if there was a treatment and / or a population effect.

how to sum columns in R?

Dear all, I'm attempting to use a piecewise regression to model the trajectory of reproductive traits with age in a longitudinal data set using a mixed model framework. The aim is to find three slopes and two points- the slope from low performance in early age to a point of high performance in middle age, the slope (may be 0) of the plateau from the start of high performance to the

dear List I have a dataset with blood measurements at 5 points in TIME (0,30,60,90,120) taken on 3 VISITS (same subjects). the interest is to compare these measurements between Visits, overall and at the different time points. I have problems setting up repeated measures ANOVA with 2 repeated measures (VISIT and TIME) (and then doing post hoc testing) or doing it with a linear mixed model ( both

hello mailing list! i still consider myself an R beginner, so please bear with me if my questions seems strange. i'm in the field of biology, and have done consecutive hydraulic conductivity measurements in three parallels ("Sample"), resulting in three sets of conductivity values ("PLC" for percent loss of conductivity, relative to 100%) at multiple pressures

I'm trying to figure this out with "Writing R Extensions" but there's not a lot of detail on this issue. I want to write a (very simple really) C external that will be able to take "..." as an argument. (It's for optimizing a function that may have several parameters besides the ones being optimized.) I got the "showArgs" code (from R-exts) to compile and

I am interested in testing two similar nls models to determine if the lines are statistically different when fitted with two different data sets; one corn, another soybean. I know I can do this in linear models by testing for interactions. See Introductory Statistics with R by Dallgaard p212-218 for an example. I have two different data sets I am comparing to lai. ci.re should have very