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Hi, every body! I am a new comer for R, so my question would unavoidablely sounds stupid. Sorry! In my experiment, there are two type of soil ( soil F and soil D), each half of them were subjected to steam sterilize (result in FS and DS soil). A equal volume of soil from two of the four soil types (F, D, FS, DS) were mixed as follows: F+F, F+D, F+FS, F+DS, D+F, D+FS, D+DS, FS+DS (eight

I am trying to run the following model in R > lmer(leaves.eaten~Geocytotype+(1|TEST/ PLANT),data=cyphoplantfeeding,family=poisson) My experimental setup is 41 replicates (TEST) of an experiment in which there are three Geocytotypes of a plant species in each TEST, and two plant pseudoreplicates per Geocytotype in each test (i.e. 3*2=6 plants per test). So my random factors are trying

Hi everyone, I have a question about calculating r-squared in R. I have tried searching the archives and couldn't find what I was looking for - but apologies if there is somewhere I can find this... I carried out a droughting experiment to test plant competition under limited water. I had: - 7 different levels of watering treatment (1 -7 - from most watered to least watered/) - 15

Dear R-people, I hope asking this is not too cheeky, but I do have a R Problem. I hope that some of you like to play around with R and can help me. Its like this. I have several plant species (A,B,C) and 10 replicates per species. 5 plants per species are damaged, 5 not. I let a caterpillar feed on each plant and measured the growth of the caterpillars on control plants (CR) and on damaged

Hi, I'm using metafor to perform a mixed-effects meta-analysis. I'd like to test whether the effect is different for animals and plants/whether "group" (animal/plant) influences the effect size, but am having trouble interpreting the results I get. I've read previous posts about QM in metafor, but I'm still a bit confused. I've dummy-coded the factors:

Hola a todos: Necesito saber si alguien tiene alguna idea de un paquete con múltiples funciones (cálculos) para determinar el tamaño de la muestra (particularmente de estudios de psicología y ciencias sociales). De antemano agradezco la atención. Saludo desde Brasil *Guilherme Amorim Homem de Abreu Loureiro* Agronomist Engineer *CREA-BA: 051511013-2* Master of Science in Crop Production, Soil

Hi, list, I have got a dataset on soil and plant. I would like to fit a "glm" to my data. My response variable is percentage data. That is percent of plant root length colonized by Arbuscular micorrhiza fungi. Because of the nature of my data, I am not quite sure whether gamma or gaussian distribution is suitable for this type of data. If I use gamma distribution, which link function is

I saw different specifications for Random Effects and I'm confused about the use of "/" and the use of "(0+...|)" . Let say we have a nested structure where some countries have some several plants in different states and we measure the reaction to a drug. The list of Countries = USA, France, Italy The States for USA = Michigan, Florida, California The States for France

Hello everybody I want to compare the proportions of germinated seeds (seed batches of size 10) of three plant types (1,2,3) with a glm with binomial data (following the method in Crawley: Statistics,an introduction using R, p.247). The problem seems to be that in two plant types (2,3) all plants have proportions = 0. I give you my data and the model I'm running: success failure

Hi folks, I have 25 stand height observations over 7 years period and daily leafbiomass data during this period. I want to use the 25 plant height observations as inputs and predict the daily stand height during the 7 years. SH=matrix(data=NA , nrow = 2641, ncol = 1) for (i in 1:2641) { SH<- predict(lm(height~Date, data=Stand_Height)); dl=leafbiom$Date[i-1]; de=leafbiom$Date[i];

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, Based on par function, I can split the screen into two parts left and right. I wish x occupies the half left screen, and all plants occupy half right screen, which happens right now. But I wish the right screen, to be split in 3 or more vertical parts where each pair of the same type of plant, are together in its own block of boxplot, because each plant has its own unit of measure.

Dear list, I would like to apply my own colours to a stacked area plot, done with qplot, but I have not succeeded... What do I have so far (I am dealing with the development of cover of specific groups of plants): library(ggplot2) library(RODBC) channel <- odbcConnect("myusername", case="tolower") sql <- "select trial, cover_of, dateofsurvey, cover from

Hi, I tried to do a nested Anova with the attached Data. My response variable is "survivors" and I would like to know the effect of (insect-egg clutch) "size", "position" (of clutch on twig) and "clone" (/plant genotype) on the survival of eggs (due to predation). Each plant was provided with three different sizes of clutches (45,15,5) and had

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 I would like to know how to pivot a table that will sum the number of plants (a or b) for each location (x,y,z) I have read on the listserve similar questions but which involve summing up numbers rather than factors. I have also read about the R package reshape on the listserve but wanted to know if there's a way to do it easily without the package Thanks for the help! location plant x

Hi, I am new to this list as a poster, but a reader for some time. I've using R for several weeks now, and I have a lot of questions about certain procedures. Here I go: I want to test if there are differences in the time spent by pollinators visiting flowers of a given plant species, according to a number of experimental manipulations made on those flowers. All experimental

Hi, I would like to construct a transition matrix from a data frame with annual transitions of marked plants. plant<-c(1:6) class<-c("seed","seed", "seed", "veg", "rep", "rep") fate<-c("dead", "veg","veg","rep", "rep", "veg") trans<-data.frame(plant, class, fate)

I am trying to obtain adjusted means and standard errors for a three way ANOVA I have three effects, two continuous; fire frequency and annual precipitation, and one categorical; soil type in an unbalanced design. I am testing the effect of annual precipition (AP), soil type (ST), and fire frequency (FF) on stem count (SCt) My data table looks as such: ST FF AP SCt 3 Coy

Hello, I am having a problem with the zero-inflated negative binomial (package pscl). I have 6 sites with plant populations, and I am trying to model the number of seeds produced as a function of their size and their site. There are a lot of zero's because many of my plants get eaten before flowering, thereby producing 0 seeds, and that varies by site. Because of that and because the