similar to: How to calculate the correct SE in a nested or spliplot anova?

Sorry for bothering you - but I have a little problem. I`m completely new in R and trying to use lmer. That works, but I m not sure if my code is right, so I would just like to get an opinion from the experts. I have a Growthrate of plants (RGR Fixed Factors: Fertilizer, Status (alien or native plants) and their interaction Random Factors: Age is a covariable; than I have plantfamily and

Dear R Community, Below is a problem with a simple ggplot2 graph. The code returns the error message below. Error: stat_count() must not be used with a y aesthetic. My code is below and the data is attached as a ?text? file. # Graph of the probabilities library(digest) library(DT) datatable(probability) str(probability) probability$Fertilizer <- as.factor(probability$Fertilizer)

Hi James, If you want to specify the y-values, you need to use stat="identity" as below: ggplot(probability, aes(x=Fertilizer, y=prob)) + geom_bar(stat="identity", aes(fill=Treatment)) best, huzefa On Tue, Apr 12, 2016 at 1:02 PM, James Henson <jfhenson1 at gmail.com> wrote: > Dear R Community, > > Below is a problem with a simple ggplot2 graph. The code

Hello R-help, I'm studying an example in the R book.? The data file is available from the link below.http://www.bio.ic.ac.uk/research/mjcraw/therbook/data/fertilizer.txt Could you explain Why the results from lme() and lmer() are different in the following case? In other examples, I can get the same results using the two functions, but not here...? Thank you.Miya library(lme4)library(nlme)#

Dear R folk, First off I want to thank those of you who responded with comments for my R quick and dirty stats tutorial. They've been quite helpful, and I'm in the process of revising them. When it comes to repeated measures MANOVA, I'm in a bit of a bind, however. I'm beginning to see that all of the documentation is written for psychologists, who have a slightly

Hi all, I analysed my data with lme and after that I spent a lot of time for mean separation of treatments (post hoc). But still I couldn’t make through it. This is my data set and R scripts I tried. replication fertilizer variety plot height 1 level1 var1 1504 52 1 level1 var3 1506 59 1 level1 var4 1509 54 1 level1 var2 1510 48 2 level1 var1 2604 47 2 level1 var4 2606 51 2 level1 var3

r-help at stat.math.ethz.ch on Wednesday, October 26, 2005 at 6:00 AM -0500 wrote: Ronaldo, Try Harold's suggestion. The df still won't agree, because lmer (at least in its current version) just puts an upper bound on the df. But that should be OK, because all those t tests are approximations anyways, and you can get better confidence intervals (credible intervals, whatever) by using the

Hello I am analysing aboveground biomass data from revegetation testplots which I constructed in a split-plot design using the function lme. For the experiment, the three factors are amelioration (2 levels), fertilizer (2 levels) and treatment (7 levels). Each testplot (block) has a singlereplicate of each treatment (total of 8 testplots). The blocks were constructed of topsoil. Each block was

Hello everyone I am currently trying to conduct analysis of my graduate thesis data using a mixed effects model and I have reached an impass. When I try to conduct a multiple comparison, I get an error (See below): > fm3<- lme(abovegroundbiomass.m.2~medium*amelioration*fertilizer*treatment, random=~1|block/medium/amelioration/fertilizer) > tukeytest<-glht(fm3,

Hi there, I have a experimental design related question. I have done a experiment with 3 factors. The design matrix is similar to: > data.frame(Factor.1 = rep(rep(0:2, each = 3),3), Factor.2 = rep(c("U","S","N"), 9), Factor.3 = rep(0:2, each = 9)) Factor.1 Factor.2 Factor.3 1 0 U 0 2 0 S 0 3 0 N

Windows 2000 . 5.00.2195 with Service Pack 1. R 1.5.1 Output from my split-split plot aov "alerted" me that I have done something wrong. I designed an experiment with all combinations of all levels of each treatment, but lost a little data (3 out of 192 plots). With the following data, I run the following model: > collim[c(1:6,187:192),c(1,3:6,9)] plot Litter Fert

Hi everyone! I tried to look up in the previous topics whether there was something similar to my question but I think there's nothing corresponding... Anyway! Here is my problem: I have a plot (qplot()) in which I want to insert axis labels with the following text: kg NH4+ N-equiv. * ha-1 yr-1 (well... 4 smaller and down and + as a power (the same for the -1) but I am sure you understood

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)

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Hi, I have this: lme(y~x1+x2,random=~1|x1/x2) How to make this random effect using lmer? I try this: lmer(y~x1+x2+(1|x1/x2) But it dont work. Any idea? Thanks Ronaldo -- System halted! -- |> // | \\ [***********************************] | ( ?? ?? ) [Ronaldo Reis J??nior ] |> V [UFV/DBA-Entomologia ] | / \ [36570-000 Vi??osa -

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Peter Dalgaard writes (in response to a question about 2-way ANOVA with imbalance): > ... There are various > boneheaded ways in which people try to use to assign some kind of > SumSq to main effects in the presence of interaction, and they are all > wrong - although maybe not very wrong if the unbalance is slight. People keep saying this