similar to: Two Level Nested ANOVA

First of all thank you for the responses. I appreciate the suggestions i have received thus far. Just to reiterate I am trying to analyze a data set that has been collected from a hierarchical sampling design. The model should be a mixed model nested ANOVA. The purpose of my study is to analyze the variability at each spatial scale in my design (random factors, variance components), and say

Hello all. This may be a trivially simple question to answer, but I'm a little bit stumped with respect to the calculation of the F statistics in nested anovas in R. If I understand correctly, the F statistic for the among-subgroups but within groups hypothesis is calculated as MS_subgroups/MS_error, while the F statistic for the factor is calculated as MS_factor/MS_subgroups (I'm

Hi, there I am not a member on your mailing list, so could you please cc: a response to me? I am currently attempting to perform an ANOVA with both nested and normal factors. My problem is that R is treating my nested factors the exact same way as it would interaction terms. My output for the nested model is as follows: > nested <- anova(lm(ltotinv ~ habitat + fish/lake +

I have an ANOVA model with 2 factors "Environment" and "Site", "Diameter" is the response variable. Site should be nested within Environment. Site is also a random factor while Environment is fixed. I can do this analysis using the "aov" function by using these commands: >model<-aov(Diam~Env+Error(Env%in%Site),data=environ) >summary(model)

Hello R List: My problem is with a nested anova. I have read the r-help and it has answered some of my questions but i still need some help on this one. I have also posted for help on this data set before, so i apologize in advance for any repetition. My design is as follows: response: Quadrat Counts (individuals per quadrat) Explanatory: Region (3 regions) Locations (4

Hi, there I first sent this e-mail a couple months ago, to no avail.Since I am not a member on your mailing list, so could you please cc: a response to me? I'll be sure to check the list today for replies. I am currently attempting to perform an ANOVA with both nested and normal factors. My problem is that R is treating my nested factors the exact same way as it would interaction terms.

hello R help I am trying to analyze a data set that has been collected from a hierarchical sampling design. The model should be a mixed model nested ANOVA. The purpose of my study is to analyze the variability at each spatial scale in my design (random factors, variance components), and say something about the variability between regions (fixed factor, contrast of means). The data is as

Hello, I have been trying to get an ANOVA table for a linear model containing a single nested factor, two fixed factors and a covariate: carbonmean<-lm(C.Mean~ Mean.richness + Diversity + Zoop + Diversity/Phyto + Zoop*Diversity/Phyto) where, Mean.richness is a covariate, Zoop is a categorical variable (the species), Diversity is a categorical variable (Low or High), and Phyto (community

Hi list, I have some anova issues... I have a dataset comprised of two factor values and a dependent value. The factors are patchiness and within patchiness I have 4 treatments. So factor treatment is nested within factor patchiness. The dependent variable is a lenght. If I'm not mistaken my model would be: model <- aov(length ~ patchiness + patchiness/treatments) However there are

Hello. I am new to R. And, I want to perform a multiple nested anova on a large datasets (with 9448 observations). Under the helps from R-Sig-ecology mailing list, I have gained many progresses. But I still have some confusions. I want to ask for some helps here. my dataset("SeedL.txt") was not attached. Data are not sorted by factors. In this dataset, "SpecN"

I have the following results for an ANOVA comparing two nested models. I wasn't sure how I am supposed to report this result in the area of psychology. Specifically, am I supposed to report the DF's or just the F ratio? I could manually calculate the degrees of freedoms, but there must be a reason why R does not give this information, i.e. those are not conventionally used in the

I am having trouble setting up a nested anova model. Here is a truncated version of my data: > data Ind Treatment PC1 1 PER14 SC 1.14105282 2 PER14 SH 1.45348615 3 PER14 AC 2.45096904 4 PER25 SC 1.23687887 5 PER25 SH 4.54797450 6 PER25 AC -0.73391131 7 PER30 SC 1.15899433 8 PER30 SH 2.83273736 9 PER30

Hello, I have been trying to get an ANOVA table for a linear model containing a single nested factor, two fixed factors and a covariate: carbonmean<-lm(C.Mean~ Mean.richness + Diversity + Zoop + Diversity/Phyto + Zoop*Diversity/Phyto) where, *Mean.richness* is a covariate*, Zoop* is a categorical variable (the species), *Diversity* is a categorical variable (Low or High), and

Dear R user I have 2 problems with lmer. The statistical consultance service of my university has recomended to me to expose those problems here. Sorry for this quite long message. Your help will be greatly appreciated... Gilles San Martin 1) anova() I fit a first model : model1 <- lmer(eclw~1 + density + landsc + temp + landsc:temp + (1|region) + (1|region:pop) + (1|region:pop:family),

Hi, I'm trying to work through a Nested ANOVA for the following scenario: 20 males were used to fertilize eggs of 4 females per male, so that female is nested within male (80 females used total). Spine length was measured on 11 offspring per family, resulting in 880 measurements on 80 families. I used the following two commands: summary(aov(Spinelength ~ Male*Female)) and

Dear R-users, I have 3 plant populations (fixed). Within each population there is the same number of “families” (random) – the seed progeny of the same plant. These families were exposed to 2 treatments (fixed) and their response was measured (mean values for 25 seedlings per family per treatment are presented in data table). I would like to know if there is a significant difference in the

I have taken the liberty of including the R-help mailing list on this reply as that is the appropriate place to discuss lmer results. On 4/5/06, Andreas Svensson <andreas.svensson at bio.ntnu.no> wrote: > Hello again > I have now recieved some helpful hints in this matter and will summarize them but first let me reiterate the problem: > > I had two treatments: 2 types of food

Dear All, I sent already before a message concerning Levene's test in nested model, but I didn't get any answer. Optimistically I hope to get an answer this time. I also point a new question related to the whole model, because I haven't find any sure answer if I am analysing it in a suitable way or not. I really have tried to do my homework. I have response variable (y) and four

Hi All, I am frustrated by mixed-effects model! I have searched the web for hours, and found lots on the nested anova, but nothing useful on my specific case, which is: a random factor (C) is nested within one of the fixed-factors (A), and a second fixed factor (B) is crossed with the first fixed factor: C/A A B A x B My question: I have a functioning model using the aov command (see

Hello, Why does anova.lm sometimes return a p-value and at other times not ? Is it because it recognizes nested models from non-nested ones ? > x<-seq(1,100,1) > y<-3*x+rnorm(100) > anova(lm(y~x),lm(y~x+I(x^2)),test="F") Analysis of Variance Table Model 1: y ~ x Model 2: y ~ x + I(x^2) Res.Df RSS Df Sum of Sq F Pr(>F) 1 98 90.449 2 97 90.288 1