search for: habitats

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

I have been working on the following code but keep getting an err message. My current thinking is that the problem is on the indexing but do not know how to fix it. Any help please? ungulate <- read.csv("Ungulate.csv",row.names=1) ungulate <- as.matrix(ungulate);colnames(ungulate)<-NULL;rownames(ungulate)<-NULL habitat <- read.csv("Ungulate_vegetation.csv")

...I am trying to assess variance components for a nested, mixed-effects model. I think I got an answer that make sense from R, but I have a warning message and I wanted to check that what I am looking at is actually what I need: my data are organized as transects within stations, stations within habitats, habitats within lagoons. lagoons: random, habitats: fixed the question is: how much variation is due to lagoons? habitats? lagoons*habitat? transects? Here is my code: res <- aov(COVER ~ HABITAT + Error(HABITAT+LAGOON+LAGOON/HABITAT), data=cov) summary(res) and I get Sum Sq for each to cal...

Dear All, I would like to make partial sums (or means or any other function) of the values in intervals along a sequence (spatial transect) where groups are defined. For instance: habitats<-rep(c("meadow","forest","meadow","pasture"),c(10,5,12,6)) observations<-rpois(length(habitats),2) transect<-data.frame(observations=observations,habitats=habitats) aggregate() is not suitable for my purpose because I want a result respecting the o...

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.

...2 0.0235207 habitat:site:Gear 12 39.244 3.2704 3.1930 0.0003546 Residuals 186 190.505 1.0242 What exactly does this outcome mean? It looks like there are differences between gears and sites, but not among habitats. Which gear is better, which site is better, which gear works better in each site, etc.? I?ve looked for some post hoc code to do this, but I can?t find anything and I am at wits end. Thanks, Rick M. -- View this message in context: http://r.789695.n4.nabble.com/nested-anova-tp3006469p3006469...

Hi, I'm working on the codes below however every time I run them when they get to OpenBUGS I keep getting the error message: array index is greater than array upper bound for hab. Any help would be greatly appreciated, Suzie Codes: ungulate <- read.csv(file.choose ()) #ungulate ungulate <- as.matrix(ungulate);colnames(ungulate)<-NULL;rownames(ungulate)<-NULL

hi all, I often have a data frame like this example data.frame(sq=c(1,1,1,2,2,3,3,3,3),area=c(1,2,3,1,2,3,1,2,3),habitat=c("garden","garden","pond","field","garden","river","garden","field","field")) for each "sq" I have multiple "habitat"s each with an associated "area". I

...ild ~ a$habitat/a$treatment/a$trial) Residuals: Min 1Q Median 3Q Max -58.905 -19.958 -5.774 16.693 88.890 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 55.4664 2.0332 27.281 < 2e-16 *** a$habitats -11.9615 2.8753 -4.160 3.26e-05 *** a$habitate:a$treatmentc 7.3581 2.8753 2.559 0.01054 * a$habitats:a$treatmentc -4.9803 2.8753 -1.732 0.08335 . a$habitate:a$treatmentp -13.9906 2.8753 -4.866 1.19e-06 *** a$habitats:a$treat...

Why are the results not reliable? ________________________________ From: ESCHEN Rene [mailto:rene.eschen@unifr.ch] Sent: Wednesday, August 23, 2006 3:48 AM To: Spencer Graves; r-help@stat.math.ethz.ch Cc: Doran, Harold Subject: RE: [R] Random structure of nested design in lme The output of the suggested lmer model looks very similar to the output of aov, also when I ran the model

I have two data sets with locations, X, Y of houses (df.house) and habitats(df.habitat), respectively. In each dataset, there are 3 replicates (Repeat). Because each replicate has different locations of houses and habitats, I would like to plot them in panels. I wrote something like this: mypanel<-function(x,y,subscripts,...){ panel.xyplot(x,y,pch=20) panel.xypl...

Hi, I'm trying to use adonis on a subset of data from a dataframe. The actual data is in columns 5:118, and the first four columns are various factors. There are 3 levels of the factor Habitat, and I want to examine differences among only two of them. So I started with: > CoastNear = subset(gel_data, Habitat != "I") The resulting data.frame has three levels for Habitat, but

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 +

Hi, I have three years of species presence/absence data for a set of ~100 ponds, with a list of associated habitat characteristics (park, vegetation, hydroperiod, etc.). The datasets differ slightly by year because some ponds were dry in some years and not in others. My goal is to look at habitat associations for a couple focal species. For each year, I have a data table that looks like

...I am fresh out of ideas. I have carried out a Kruskal-Wallis test to compare breeding strategy variance of my study organisms (rank data, therefore non-parametric, in oder of increasing degree of "terrestrialization", in this case: adaptations to breeding on land as opposed to in aquatic habitats) between habitat groups (I, II and III). Subsequently I would like to do a "Post-Hoc test" or in other words a set of corrected pair-wise comparisons to test the relationship between individual groups. For this I would like to use the Nemenyi-Damico-Wolfe-Dunn test in the "coin"...

Hi all, I have some concerns regarding the rasterize option in R and I would like to know if the fun=max in rasterize in R provides similar results to the one achieved by using "Polygon to Raster using maximum-combined-area" in ArcGIS? I'm trying to rasterize a habitat layer to a raster of 10m spatial resolution using the function 'max' (e.g. r <- rasterize(ht, r,

Hi all, This is partly a statistical question as well as a question about R, but I am stumped! I have count data from various sites across years. (Not all of the sites in the study appear in all years). Each site has its own habitat score "habitat" that remains constant across all years. I want to know if counts declined faster on sites with high "habitat" scores. I can

All, I'm trying to analyze the results of a reciprocal transplant experiment using lme(). While I get the error-term right in aov(), in lme() it appears impossible to get as expected. I would be greatful for any help. My experiment aimed to identify whether two fixed factors (habitat type and soil type) affect the development of plants. I took soil from six random sites each of two types

Hi! I am trying to know which habitat variables most affect bird counts in a radius of 100m. I obtained bird counts in 2751 spatial points, and measured percentage of 21 habitat variables in these points. I applied a mixed model using the "lmer" function to these data, but I do not know how to select the best model using AIC here. Is there a way to do this automatically with R?

Dear all, I would like to add mixed effects in a multinomial model and I am trying to use MCMCglmm for that. The main problem I face: my data set consits of a trapping data set, where the observation at eah trap (1 or 0 for each species) have been aggregated per traplines. Therefore we have a proportion of presence/absence for each species per trapline. ex: ID_line mesh habitat Apsy Mygl