search for: gaiarrido

Hello, I want to stop receiveng mails from R help forum, thanks. This is my data : Mario Garrido Escudero Dpto. de Biología Animal, Ecología, Parasitología, Edafología y Qca. Agrícola Fac. de Farmacia Campus Unamuno Universidad de Salamanca gaiarrido@usal.es [[alternative HTML version deleted]]

Hi, I?m trying to move to ubuntu at all, but I don?t like R in Ubuntu because it runs in the terminal, so i can?t access directly to some options R gots in Windows. Is there any R can i install in ubuntu which runs in hos own prompt or terminal?? Thanks ----- Mario Garrido Escudero PhD student Dpto. de Biolog?a Animal, Ecolog?a, Parasitolog?a, Edafolog?a y Qca. Agr?cola Universidad de Salamanca

Hello, I?m starting with my PhD and I have to stop because i got a little knowledge in R and statistics. I?ve got a model of this kind: binary response variable: prevalence of infection (0/1) 3 categorical independent variables: sex, month and name of the area I was trying with a full model like this, before the simplification model<-aov(prevalencia~sex*month*area) but the Fligner test

Hi, I?ve got this model > model<-glm(prevalence~agesex+agesex:month,binomial) and the output of anova is like that > anova(model,test="Chisq") Df Deviance Resid. Df Resid. Dev P(>|Chi|) NULL 524 206.97 agesex 2 9.9165 522 197.05 0.007025 ** agesex:month 9 18.0899

Hi, I?ve got some problems with the labels of the x-axis I,ve got two factors with two categories each: sex (males and females) and area (central and peninsulae), but because of the lenngth in the graphic just appeared two of the four labels. I thought the solution could be rotate it 45? degrees, I have read it can be done with "srt" or "rotate", but I don?t know hoe to use

When I try to adjust a mixed model with random effects I can make this order without problem > lm.FA<-lme(absFA~trait*condition,random=~1|individual) But if I try to fit a model in which the response (absFA) is not the same in all individuals at different levels of "trait" factor , but varies randomly from each. That is, this order >

nobody? please ----- Mario Garrido Escudero PhD student Dpto. de Biolog?a Animal, Ecolog?a, Parasitolog?a, Edafolog?a y Qca. Agr?cola Universidad de Salamanca -- View this message in context: http://r.789695.n4.nabble.com/interpreting-repeated-measures-mixed-model-tp4647652p4647689.html Sent from the R help mailing list archive at Nabble.com.

Hi, I'm trying to make a model in order to know wich factors got?s influence in the intensity of a infection, but just in the individuals who's got this infection. In my data I've got a variable called "prevalence" with 2 levels: 1.- Infected individual 0.- Non infected So what i'm trying to do is a subset in a model like this,

Hi, somebody can help me. Idon't understand very well the manual of the this package, I suppose I must enter "wdtxtStart", before I start working, but is supposed that this command should open Word, but nothing happens. I use Rgui, not Rcmdr. Thanks ----- Mario Garrido Escudero PhD student Dpto. de Biolog?a Animal, Ecolog?a, Parasitolog?a, Edafolog?a y Qca. Agr?cola Universidad de

Hi R-users, I need to run Filliben correlation test, but I'm not able to find this function in any package. Perhaps it isn't in a package, but sometimes anybody have program this function or create a routine to estimate it. I found it in google and I hope what I found it's in this page, http://genepi.qimr.edu.au/staff/davidD/R/filliben.R but i can't open it. Anybody can help me?

I've read something about this problem, but I don't know how can i avoid this problem. Why the order of the factors give different results? I suppose it's because the order of the factors, i've just changed "lcc" from the first position to the last in the model, and the significance change completely >

I've made fligner test with the same data, changing the orders of the variables, and this what i get > fligner.test(rojos~edadysexo*zona*ano*estacion) Fligner-Killeen test of homogeneity of variances data: rojos by edadysexo by zona by ano by estacion Fligner-Killeen:med chi-squared = 15.7651, df = 2, p-value = 0.0003773 > fligner.test(rojos~ano*edadysexo*zona*estacion)

Hi, I'm working with R in windows and I wonder if there is any command (of the kind CTRL+ ) to transfer the commands I've worked with (like: > model<-glm(prevalencia~edadysexo*mes*zona,binomial)) to a script automatically, without the results I received from R after execute them. Another question, what's the combination of CTRL+ for transfer the orders in the other way, fom the

Hi, I,ve a run a model like this mcrm<-glm(catroj~month,binomial) being catroj a binary response variable with two levels (infected and non infected) > anova(mcrm3,test="Chisq") Df Deviance Resid. Df Resid. Dev P(>|Chi|) NULL 520 149.81 mes 3 16.86 517 132.94 0.0007551 *** When I?m trying to do a post

Hi, i?ve read all that i could about the post-hoc test for kruskall-Wallis, now i know that i need to run Duncan test, but i?m not able to find in any package or script. I s anybody knows where can i find it? Thanks ----- Mario Garrido Escudero PhD student Dpto. de Biolog?a Animal, Ecolog?a, Parasitolog?a, Edafolog?a y Qca. Agr?cola Universidad de Salamanca -- View this message in context:

Hi, i was working with this model > mq<-glm(rojos~edadysexo*zona*estacion,quasipoisson) and i get this minimal adequate model > anova(mq5,test="F") Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL 518 64799 edadysexo 2 1556.5 516 63243 8.9434 0.0001524 *** zona 4

i ran this model > model2<-glm(rojos~ageandsex+sector+season+sector:season,quasipoisson) > glht(model2,linfct=mcp(ageandsex="Tukey")) General Linear Hypotheses Multiple Comparisons of Means: Tukey Contrasts Linear Hypotheses: Estimate M - H == 0 0.2898 SUB - H == 0 -0.2261 SUB - M == 0 -0.5159 I tried to do the same changing factor season

Hi, I've got this model and following Hothorn et al advices, I used glht for a post hoc comparison > modezqM<-glm(rojos~estacion*zona3,quasipoisson,subset=(edadysexo=="M")) > anova(modezqM,test="F") Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL 293 41148

I try to fit a repeated measures model, in which: FA: The difference in the number of scales between the left and right sides for a given trait trait: the each of the measured features are 6 for each individual Condition: is the state of condition of each individual Individual: Each of the specimens studied By adjusting the model happens to me the following >

I've run an ancova, edadysexo is a factor with 3 levels,and log(lcc) is the covariate (continous variable) I get this results > ancova<-aov(log(peso)~edadysexo*log(lcc)) > summary(ancova) Df Sum Sq Mean Sq F value Pr(>F) edadysexo 2 31.859 15.9294 803.9843 <2e-16 *** log(lcc) 1 11.389 11.3887 574.8081 <2e-16 ***