similar to: PerMANOVA of community data

Hi! Thanks for providing great help in R-related statistics. Now, however I'm stuck. I'm not a statistics person but I was recommended to use R to perform a nmds plot and PerMANOVA of my dataset. Sample(treatment) in the columns and species (OTU) in the rows. I have 4 treatments (Ambient Temperature, Ambient temperature+Low pH, High temperature, High temperature+low pH), and I have 16

Hello, I want to perform a permanova where the first factor called Treatment has four levels. The second factor involves sampling the same research plots for four consecutive years, hence the repeated measurements. I have been able to use the adonis function from the package vegan to run this analysis. code below: TC.perMANOVA.adonis<-adonis(TC.PerMANOVA ~ Treatment*Year,

Hello, I would like to use a permanova to analyze my repeated measures, multivariate data set using the package vegan (adonis function). I have several explanatory variables and many clinical biochemistry/hematological response variables (all continuous, non-normally distributed). My explanatory variables are: ID - 29 levels - individual subjects Treatment - 2 levels Sex - 2 levels Time -

Hi everyone! I have data consisting of several response variables and several explanatory variables. I wish to do a permanova on this using the vegan library and the adonis() function. However, my data had several missing values in it. In order to 'fix' this I used the mice() function from the mice library to make 5 imputations for all the missing values. To do analysis on the 5 datasets

Dear Thomas, The head of my dataset > head(wsuv) parcel sp time censo treatment species 1 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 2 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 3 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 4 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1

Dear all, I am trying to get a PERMANOVA with quite large data set. I am reading a lot about this question, but I do not get the answer about it. Although I know that the R function is adonis () (vegan package), it does not work: adonis(Pha.env~SPha, data=Pha, permutations=10) The error message: Error: cannot allocate vector of size 334.2 Mb In addition: Warning messages: 1: In vegdist(lhs,

Dear list members, I am new member and fairly new into R world! I hope what I have is not beyond the purpose of this list. I did first search for similar experimental designs without success. I want to perform an ANOVA analysis using the aov() function. I am not 100% sure that I have it right. If anyone can help me, that will be greatly appreciated. My design is not balanced for any of the

Hi everyone, I am trying to analyse my data from a small plant experiment (for a meeting tomorrow afternoon) and am a beginner to R so I apologise if this is a very basic question. I carried out a plant experiment examining plant interactions between two species (A and B) under different watering treatments. I had: - 7 watering treatments (7 different watering frequencies labelled 1-7) - 3

Hi everybody, I am trying to fit a model with the lmer function for mixed effects. I have an experimental design consisting of 5 field plots. Each plot is divided in 12 subplots where the influence of three factors on the growing of tree seedlings is tested: (1) seed (1 = presence; 0 = absence); (2) seedling species (oak holm vs. pine); (3) treatment (three different treatments). In each of

Dear All! It's now weeks that I'm going crazy with R, and as I'm a new user I now ask for help (also because I still have only a few days to finish..)... So shortly I describe you my Experiment in which I was looking for the decomposition of herbivore dung under different treatments: I made a box design experiment which is structured in the following way: I collected dung from 2

Hi R-people, I performed controlled experiments to evaluated the seeds germination of two palms under four levels of water treatments. I conducted a generalized linear model (GLM) with a Poisson distribution to verify whether there were significant differences in the number of seed germination (NS-count variable) between treatments and species (explanatory variables). Thus, my model and output

I am a beginner with R and have managed to use vegan to run a CCA on my data. I am evaluating the habitat relationships of select species in riparian areas around creeks before and after logging across three sampling intervals (pre-logging, two-years post-logging,. and 10 years post-logging). I sampled from 18 sites of 3 treatments (n = 6 sites for each treatment). When I plot my

Hi, I wonder if anyone can help me with specifying a right model for my analysis. I am a beginner to lme methods and though have spent already many hours studying from various books an on-line helps, I was unfortunately not able to find a solution to my problem on my own. Data structure: I studied escape behavior of three species of a prey to a predator. The prey specimens (many) were in a

Greetings, I am new to R and am hoping to get some tips from experienced R-programmers. I have a dataset that I've read into R as a dataframe. There are 5 columns: Plot location,species name, a species number code (unique to each species name), abundance, and treatment. There are 272 plots in each treatment, but only the plots in which the species was recorded have an abundance value. For

Dear R users, I have been having problems getting believable estimates from anova on a model fit from lmer. I get the impression that F is being greatly underestimated, as can be seen by running the example I have given below. First an explanation of what I'm trying to do. I am trying to fit a glmm with binomial errors to some data. The experiment involves 10 shadehouses, divided between

Hello, I'm attempting to analyze a split-split plot model, currently using lmer. My design is similar to that used in Casella's Experimental Designs Ozone Example (example 5.7, p 197), but I have been unable to find any coding help for split-split plot models through searches of several textbooks and the R list serve. I have three treatments of interest (A,B,C), each with 2 treatment

Hi all, I have site data with plant species cover and am looking for trends. I'm kind of new to this, but have done lots of reading and can't find an answer. I tried decorana (I know it's been replaced by ca.) and see a trend, but I'm not sure what it means. Is there a way to get the loadings/eigenvectors of the axes (like in PCA)? Is there a way to do this with rda() too? How

Hi All, I have a large data set with many columns of data. One of these columns is a species identifier and the remainder are variables such as temperature or mass. Currently I am carrying out a single regression on subsets of the data set, e.g. separated data sets with only the data from one species at a time. I have been searching for a thread that will help me to understand how best to repeat

Hello, I have used R in the past to conduct multiple comparisons on standard linear models, but am a bit confused as to how to go about doing it with a mixed effects model. I am conducting a bioindication study using carabid beetles in which I have four treatment types (forest harvest types with varying levels of canopy structure retention), and am using canopy closure percent as a covariate in

Many thanks for your responses. I realize I made the first-time-poster's error of not giving an example of the data. There actually are no NA values, so I'm not simply replacing values in the data frame. So, the number of species (and therefore abundance values) listed in each treatment differs, even though they all have the same number of plots sampled. Sample_ID Spec_num Species_ID