similar to: split plot design with missing plots

Windows 2000 (v.5.00.2195), R 1.5.1 I have an lme object, fm0, which I examine with anova() and intervals(). The anova output indicates one of the interaction terms is significant, but the intervals output shows that the single parameter for that term includes 0.0 in its 95% CI. I believe that the anova is a conditional (sequential) test; is intervals marginal or approximate? Which should I

Using R v. 1.7.0 on Windows 2000 I would like to plot the fitted values of a model as a function of a continuous covariate, augmented with data (e.g., augPred) grouping by combinations of fixed effects. I have not been able to use augPred effectively, and am wondering if it does not handle unbalanced data (3 out of 192 missing). I include below the model and an xyplot that almost does the

Hi, I've data from an incomplete fatorial design. One level of a factor doesn't has the levels of the other. When I use lm(), the summary() return NA for that non estimable parameters. Ok, I understant it. But I use contrast::contrast(), gmodels::estimable(), multcomp::glht() and all these fail when model has NA estimates. This is becouse vcov() and coef() has different dimensions. Is

Dear R sages, I used the function rbind to combine a matrix (M) and a vector (Fert) to get a new matrix (A). This was fine. The issue is however, that the new matrix A has as its row names the name of the vector Fert, even though I set teh new vector A to have dimnames=NULL. See short code below fyi. *Fert<-c(0,1,5) * *M <- matrix(0, 2, 3) diag(M) <- c(0.3,0.5) * *A<-

Hi R users, I sent a message yesterday about NA in model estimates ( http://r.789695.n4.nabble.com/How-set-lm-to-don-t-return-NA-in-summary-td3722587.html). If I use aov() instead of lm() I get no NA in model estimates and I use gmodels::estimable() without problems. Ok! Now I'm performing a lot of contrasts and I need correcting for multiplicity. So, I can use multcomp::glht() for this.

Dear R community, I am trying to fit an nlme model where I want to estimate the fixed effects of two treatments on the parameters on the following equation Photo~(a*(1-exp(-c*PARi/a)))-b I was able to fit a simple model without covariates following the method described in Mixed-Effects Methods and Classes for S and S-PLUS, version 3.0, but when I add the covariates, I get the error "

Hi R-Helpers: I?m trying to use the function GLMM from lme4 package, (R-1.8.1, Windows 98),and I get the following error: > pd5 = GLMM(nplant~sitio+ + fert+ + remo+ + sitio:fert+ + remo:sitio+ + remo:fert+ + remo:fert:sitio + data=datos, + family=binomial, +

Hello, I am a Masters student and I am working on my thesis modelling smallholder farms using a program in R. I have modified the original code and I am having some issues with lists that I cannot figure out. Originally, I had list file defining lists such as: Param, Crop1, Crop1, Soil, etc. (ex. Param <- list() ). Their subsets were listed as Crop1$CContent for example and there was quite

Hi, I'm trying to fit a logit model to a set of data that was collected under a split plot scheme. The structure of the data is Whole plot factors: Watering Frequency (2 levels: Hi/Lo) and Fertilizer type (3 factors A/B/C) Subplot factor: slope type (2 factors up/down) Response: Proportion of infected leaves(Infected leaves/Total leaves) of the plant (2 plants recorded from each plot)

Hi I have a file saved in R, named agrexp.Rdata, shown below > agrdata fert yield 1 25 84 2 50 80 3 75 90 4 100 154 5 125 148 If I double clicked on this file, the data is displayed without problem. However if I tried to import using: > agrdata<-read.table("agrexp.Rdata") or >

Dear all I'm not sure if I did the right analysis for my specific split splot design. We are studying biomass increase with different CO2 concentrations with four different functional plant groups (e.g. grasses, herbs, broad-leafed trees and conifers). Of each functional plant group we have four species. The design is orthogonal. The design is: Blocks: 2 (climate chambers, called

Hi all R users I did a logistic regression with my binary variable Y (0/1) and 2 explanatory variables. Now I try to draw my nomogram with predictive value. I visited the help of R but I have problem to understand well the example. When I use glm fonction, I have a problem, thus I use lrm. My code is: modele<-lrm(Y~L+P,data=donnee) fun<- function(x) plogis(x-modele$coef[1]+modele$coef[2])

Dear R users, I have a dataframe with one character field, and I would like to create two new fields (columns) in my dataset, by spliting the existing character field into two using an existing substring. ... something that in SAS I could solve e.g. combining substr(which I am aware exist in R) and "index" for determining the position of the pattern within the string. e.g. if my

How do I control the text in strips? Specifically, I want to put in the ranges generated in shingle(x) where x is continuous. Thanks, Hank Martin Henry H. Stevens, Assistant Professor 338 Pearson Hall Botany Department Miami University Oxford, OH 45056 Office: (513) 529-4206 Lab: (513) 529-4262 FAX: (513) 529-4243 http://www.muohio.edu/~botcwis/bot/henry.html

Hi Rneters, I'm running a GLM model with a full factorial design in blocks and binomial error distribution. I would like to have the F values for this model but I got a message that "using F test with a binomial family is inappropriate in: anova.glm(model, test = "F")". Should I not report F statistics on this kind of analysis? I would appreciate any comment on this.

Dear all: My logistic regression model includes one qualitative and one quantitative predictor variable, aes <- glm(p.a ~ spp * log(light), family=binomial(link=logit)), where spp is abundance of 3 species and light is subcanopy light availability varying from 0 1. I want to test differences among levels of the quantitative variable at a value of x other than the current log(light)=0.

After checking the usual archives (Baron search engine) I came up nothing. It appears that ylab=expression() doesn't work in lattice? How do I put superscripts in ylab? Many Thanks, Hank Martin Henry H. Stevens, Assistant Professor 338 Pearson Hall Botany Department Miami University Oxford, OH 45056 Office: (513) 529-4206 Lab: (513) 529-4262 FAX: (513) 529-4243

Hi enthusiasts, Trying to create a single chart in lattice with different plotting definitions for the different series (two series should be drawn with lines and the other without them) I am using a dataset, which includes a grouping variable e.g. clinic with three levels, the variable "year" and a continous variable: "mct". In the graph the variable "year" is in

Dear R Core Team I've a proposal to improve drop1(). The function should change the contrast from the default ("treatment") to "sum". If you fit a model with an interaction (which ist not signifikant) and you display the main effect with drop1( , scope = .~., test = "F") If you remove the interaction, then everything's okay. There is no way to fit a

Hello, I'm actually trying to fit a gee model with 2 nesting levels since I expect a correlation between all members of a litter at a first level and between all individuals sharing a mother at a second superior level with an exchangeable matrix. I order my dataframe by both mother and litter I try several syntaxes: id= mother*litter which give the same correlation matrix as id=