similar to: problems with glht for ancova

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 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, 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 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 have some data with two categorises plus/minus (p53) and a particular time (Time) and the outcome is a continuous vairable (Result). I set up a maximum model. ancova <- lm(Result~Time*p53) > summary(ancova) .. Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.05919 0.55646 0.106 0.916 Time -0.02134 0.01785 -1.195 0.241 p53plus

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

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, 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, 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

Hi, what would be a good way of enhancing the ancova function from the HH package when using a 2 factor ANCOVA? The current behaviour for the "ancova" function from package HH is: ---------------------------------------------- | P1 || P1 || P3 || P4 | | PS | <- the lattice strip ---------------------------------------------- | x|| x ||x ||x | |

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

Dear R user: I have a question about doing ANCOVA in S-plus or R. I know that many users use lm to do the regression and check the ANCOVA. But is there a way to get the traditional Table form of the ANCOVA test through S-plus (like what we would get from SPSS or SAS)? The problem I’m interested in is whether or not there is a treatment effect on some medical measurement. I will

Hi, I'm wondering if i can use the function "TukeyHSD" to perform the all pairwise comparisons of a "aov()" model with one factor (e.g., GROUP) and one continuous covariate (e.g., AGE). I did for example: library(multcomp) data('litter', package = 'multcomp') litter.aov <- aov(weight ~ gesttime + dose, data = litter) TukeyHSD(litter.aov, which =

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

Hi! as my subject says I am struggling with the different of a two-way ANOVA and a (two-way) ANCOVA. I found the following examples from this webpage: http://www.statmethods.net/stats/anova.html # One Way Anova (Completely Randomized Design) fit <- aov(y ~ A, data=mydataframe) # Randomized Block Design (B is the blocking factor) fit <- aov(y ~ A + B, data=mydataframe) # Two Way

I initially posted this question to one of the StackExchange sites, and they suggested that I repost my problem here. After using ezANOVA as my primary way of specifying mixed ANOVAs, I've hit a stumbling block when it come to adding a covariate to the model. I am using an ANCOVA in order to determine if there is a developmental trajectory in my data; namely, I need to be able to see the

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 R-Users, I am working with sm.ancova (in the package sm) and I have two problems with the graph, which is automatically generated when sm.ancova() is run. 1-Besides of the fitted lines, the observed data appeared automatically in the graph. I prefer that only fitted lines appear. I check the sm.options, but I could not find the way that the observed data do not appear in the graph. 2-I