similar to: contrasts using adonis function

Hi, forgive me if someone has already posted about this but I have had a look and cannot find the answer, also I am very new to R and been getting the grips with this. I have been trying to use Adonis to find out if there are significant difference between groups on data that I have analyses with NMDS, and have been struggling with getting this to work and understanding what is going on. I am

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

Hi, I found that using different contrasts (e.g. contr.helmert vs. contr.treatment) will generate different fitted probabilities from multinomial logistic regression using multinom(); while the fitted probabilities from binary logistic regression seem to be the same. Why is that? and for multinomial logisitc regression, what contrast should be used? I guess it's helmert? here is an example

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

I am trying to apply a permuation-based MANOVA (Anderson 2001) to a set of morphological data from three ecomorphs of fish reared under two different conditions and measured at two points during ontogeny. I will supply a distance matrix based on Procrustes distances calculated outside of vegan. I have not found an example of a design such as this for adonis. However, I have designed my factors

Hello all, I used google and looked at the documentation to find out why the ADONIS function is called adonis (in the vegan package). I am writing a document and would like to include a abbreviation list (similar to "ANOSIM = Analysis of Similarities"). regards, Steve

Hi, I was wondering if someone can tell me what is the difference between "strata" argument (function "adonis" in "vegan" package) and using random effects in PERMANOVA+ add-on package to PRIMER6 when doing permutational MANOVA-s? Is the way permutations are done the same? Thank you very much in advance, Vesna -- View this message in context:

hello list, i'd appreciate help regarding formula expression in adonis(), package vegan. i'm interested in the effect of an impact on species composition and if this effect is the same for different sites. i have an impact survey with plot pairs, one plot with impact the other with similar ecolgical conditions but without impact, which is the control (factor1: impact). two different

Hi, perhaps this is a stupid question, but i need some help about Helmert contrasts in the Cox model. I have a survival data frame with an unordered factor `group' with levels 0 ... 5. Calculating the Cox model with Helmert contrasts, i expected that the first coefficient would be the same as if i had used treatment contrasts, but this is not true. I this a error in reasoning, or is it

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,

I am trying to apply this technique (M.J Anderson 2001) to a dataset of aquatic insect abundances. There is a sample in the unrestored and restored segement of a stream for every time period. I would like to compare the centroids of the distance matrices for the treatments up (unrestored) and dn (restored) to see if there is a difference in insect communities between the treatments. I will not

I am using RW 1.2.3. on an IBM PC 300GL. Using the data bp.dat which accompanies Helen Brown and Robin Prescott 1999 Applied Mixed Models in Medicine. Statistics in Practice. John Wiley & Sons, Inc., New York, NY, USA which is also found at www.med.ed.ac.uk/phs/mixed. The data file was opened and initialized with > dat <- read.table("bp.dat") >

Hi, Using Vegan package I was wondering if there's a way to use a distance matrix as an input for adonis (or any of the other similar hypothesis testing functions) instead of the usual species by sample table. Working in the field of microbial ecology, what I'm trying to do is to overcome the problem of having to use discrete units such as species or OTUs, which are problematic in

Hello, I have a problem with creating an identity matrix for glmnet by using the contrasts function. I have a factor with 4 levels. When I create dummy variables I think there should be n-1 variables (in this case 3) - so that the contrasts would be against the baseline level. This is also what is written in the help file for 'contrasts'. The problem is that the function

Dear R users, When fitting a lme() object (from the nlme library), is it possible to test interactions *before* main effects? As I understand, R conventionally re-orders all terms such that highest-order interactions come last - but I??d like to know if it??s possible (and sensible) to change this ordering of terms. I??ve tried the terms() command (from aov) but I don??t know if something

Hi Folks, I'm comparing some output from R with output from SPSS. The coefficients of the independent variables (which are all factors, each at 2 levels) are identical. However, R's Intercept (using default contr.treatment) differs from SPSS's 'constant'. It seems that the contrasts were set in SPSS using /CONTRAST (varname)=Simple(1) I can get R's Intercept to match

On 6/23/05, RenE J.V. Bertin <rjvbertin at gmail.com> wrote: > Hello, > > I was just having a look at the aov function source code, and see that when the model used does not have an Error term, Helmert contrasts are imposed: > > if (is.null(indError)) { > ... > } > else { > opcons <- options("contrasts") >

Hi all, I have dataset with 2 independent variable, one (x1) is continuous, the other (x2) is a categorical variable with 2 levels. The dependent variable (y) is continuous. When I run linear regression y~x1*x2, I found that the p value for the continuous independent variable x1 changes when different contrasts was used (helmert vs. treatment), while the p values for the categorical x2 and

I'm wondering which textbook discussed the various contrast matrices mentioned in the help page of 'contr.helmert'. Could somebody let me know? BTW, in R version 2.9.1, there is a typo on the help page of 'contr.helmert' ('cont.helmert' should be 'contr.helmert').

I have some doubts about the validity of my procedure to estimeate linear contrasts ina a factorial design. For sake of semplicity, let's imagine a one way ANOVA with three levels. I am interested to test the significance of the difference between the first and third level (called here contrast C1) and between the first and the seconda level (called here contrast C2). I used the following