search for: posthocs

Hello everybody, I use the sweetpotato database included in R package: data(sweetpotato) This dataset contains two variables: yield(continous variable) and virus(factor variable). Due to Levene test is significant I cannot assume homogeneity of variances and I apply Welch test in R instead of one-way ANOVA followed by Tukey posthoc. Nevertheless, the problems come from when I apply posthoc

dear all, I want to perform a posthoc test for my ANCOVA: a1<-aov(seeds~treatment*length) With summary(glht(a1, linfct = mcp(treatment = "Tukey"))) R tells me: "covariate interactions found -- please choose appropriate contrast" How do I build these contrasts? Ideally, I would like to have the posthoc test for the ANCOVA including a block-effect

Dear colleagues, In checking a function I am adding to an R package, I get the following warning pair: ... Bad \usage lines found in documentation object 'nominal': "\\method{print}{nominal}"(x, max.print = 10, posthoc = "std.pearson.residuals.sign", assoc = ifelse("univariate" list(c("N", "alpha.X2",

Hello. We have some questions concerning the statistical analysis of a dataset. We aim to compare the sample means of more than 2 independent samples; the sample sizes are unbalanced. The requirements of normality distribution and variance homogeneity were not met even after transforming the data. Thus we applied a nonparametric test: the Kruskal-Wallis-test (H-Test). The null hypothesis was

Hi there, I was hoping to post this message. Im hoping I;ve got the right spot?! Hi there, sorry for basic question but im very new to R. Im trying to run a lme model with two categorical variables, each having 6 (for the explanatory variable C.f) and 5 levels (for expl. variable D.f) respectively. The lme runs fine, summary and anova commands are ok. But now i've tried running posthoc

Dear List, are there post-hoc tests like Scheffe, LSD, etc. available after ANOVA test is performed with significant F-statistic? I have tried help.search("Scheffe"), but "No documentation found" (and I have most of packages installed). Probably there are such tests in R, and I am just searching badly... My second question is: Which test/method I should use for ANOVA-like

Hi All, I have performed a 3-way ANOVA analysis for my experimental data using aov function. My simple R funtion for this is: 3aof <- function(x){ m <- data.frame(R,S,T, x); anova(aov(x ~ R+S+T+R*S+R*T+S*T+R*S*T, m) ) } Now, I am getting P values for all the main and interactions effects. If I want to perform postdoc test on one of my main effects, say T, what method I should use (i have

Hi, I have analyzed my data using log-linear model as seen below: > yes.no <- c("Yes","No") > tk <- c("On","Off") > ats <- c("S","V","M") > L <- gl(2,1,12,yes.no) > T <- gl(2,2,12,tk) > A <- gl(3,4,12,ats) > n <- c(1056,4774,22,283,326,2916,27,360,274,1770,15,226) >

Dear R experts, I'm beginner. My question about ANOVA for unequal sample sized data should be obsolete but I can not clarify it. I have a dataset from 23 males and 18 females. I measured one condition('cond') with 4 levels. So I'd like to see main effect of gender, cond and gender by cond interaction and also postHoc test. (In fact, I have to do anova 90 times) * 1. Question

Dear R experts I am running a negative-binomial GLM (glm.nb) to test the null hypotheses that species 1 and 2 are equally abundant between site 1 and site2, and between each other. So, I have a 2x2 factorial design with factors Site (1,2) and Taxon (1,2). Since the Site:Taxon interaction is significant, I need to do the equivalent to a "post-hoc test" for ANOVA, however, the same tests

Hola, Lo primero muchas gracias a todos por vuesta habitual ayuda. Llevo meses con las funciones lmer, pero tengo un problema no se como plantear unas comparaciones multiples una vez demostrado que el factor tiene diferencias significativas. Tengo multiples opciones, Solución A: una es hacer un bonferroni a saco (pero eso me chirria ya que tego muchos datos) Solución B: Otra es utilizar glht,

Hello all, Quick question: I want to do posthoc contrasts for a linear mixed effects model. However, when trying to use the csimtest function in multcomp package I receive an error message saying it cannot find the function, even after installing and loading package multcomp. Any pointers would be greatly appreciated Daniel

Hi, I am doing a retrospective analysis on a cohort from a designed trial, and I am fitting the model fit<-glmD(survived ~ Covariate*Therapy + confounder,myDat,X=TRUE, Y=TRUE, family=binomial()) My covariate has three levels ("A","B" and "C") and therapy has two (treated and control), confounder is a continuous variable. Also patients were randomized to

Dear R experts, I'm new in R and a beginner in terms of statistics. It should be simple question, but definitely difficult to solve it by myself. I'd like to see main effect of group(gender: sample size is different(M:F=23:18) and one of condition(cond) and the interaction at each subset from 90 datasets So I perform anova 90 times using a command like below; for(i in 1:90)

Dear useRs, I'm working on multiple comparison design on two factor (2 3 levels) ANOVA. Each of the tests I have tried (Tukey, multcomp package) seem to do only with one factor at a time. fm1 <- aov(breaks ~ wool * tension, data = warpbreaks) tHSD <- TukeyHSD(fm1, "tension", ordered = FALSE) $tension diff lwr upr p adj M-L -10.000000 -19.35342

Hi! I am quiet new with R and I have some problems to perform a posthoc test with an lme model. My model is the following: >lme1<-lme(eexp~meal+time, random=~1|id,na.action=na.omit) and then i try to get a post hoc test: >summary(glht(lme1,linfct=mcp(meal="Tukey))) but I get a warning message: Erreur dans as.vector(x, mode) : argument 'mode' incorrect Thank you for your

I'm just curious . . . if effect sizes are so important, and possibly a better way of looking at results than p-values, since they don't depend on effect size (Kline,2004; Murphy and Myors, 2004), why don't any of the classical tests, like t.test or glht specified for Tukey's posthocs, return effect sizes? I say "classical" because I'm sure there may be packages out there, not in the base program, which do return effect sizes, but do they also return everything glht does, which are confidence intervals for mean differences, t-values and p-values, standard error plu...

Thanks in advance for your help. I am running a repeated measures ANOVA in r. The same group undergoes to four different treatment conditions. So, all individuals are treated with treatments A, B, C and D in four different occasions. Once I get a significant ANOVA, I first run a paired samples t-test using the code: t.test(X1,X2,paired=TRUE) #being x1 the punctuation after treatment 1 and x2 the

Hi all, I apologize for what might be a silly question. I am interested in doing a one way anova. This is not too hard in and of itself, either with anova, aov or oneway.test . However, I need to 1) get pvalues, 2) do a posthoc analysis with Tukey HSD, 3) and have (sometimes) an unbalanced design. I just can't seem to put all the pieces together. Any suggestions? Thanks in advance, Dan.

Dear all, I have a quite basic questions about anova analysis in R, sorry for this, but I have no clue how to explain this result. I have two datasets which are named: nmda123, nmda456. Each dataset has three samples which were measured three times. And I would like to compare means of them with Posthoc test using R, following please see the output: (CREB, mCREB and No virus are the name of