search for: posthoc

...weetpotato 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 test. In Tukey posthoc test I use library(agricolae) and displays me the superscript letters between virus groups. Therefore there are no problems. Nevertheless, to perform Games-Howell posthoc, I use library(userfriendlyscience) and I ob...

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 fo...

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", "uc.12", "uc.21")), list(c("N1", "N2", "N12", "uc.12", "uc.21"))), sort.key =...

...ndent 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 rejected. Now we try to find a suitable posthoc-test in order to find out which sample means actually are statistically different. 1. We think that the Behrens-Fisher-test and multiple steel test are not applicable, because they assume normality distribution as far as we know. Is that right? 2. Statistical literature suggested to do a Nemenyi-t...

..., 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 comparisons using the glht command in the multcomp package but seem to have an error with my data labelling maybe? it doesnt seem to recognise my factor levels even though I have stated them. if i can do somekind of tukeys or LSD's that would be wonderful! M1lme <- lme(logA ~ C.f * D.f, r...

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) >

...nner. 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 about constrast stuff for type III* After googling, I found a document ( https://stat.ethz.ch/pipermail/r-help/2001-October/015889.html) and it looked like make sense. This below is what I did on R and I encountered 'error message'....

...tried specifying orthogonal contrasts, but could not figure out what the interaction contrast (see Site1:Taxon1 in below example) means. Could you please advise me how to specify a meaningful interaction contrast (i.e. contrast species within sites)? Alternatively, could you recommend a way to do posthoc comparisons? Thanks for your time and kind regards Maya > library(MASS) > counts <- c(1, 4, 9, 2, 1, 4, 2, 4, 1, 3, 2, 2, 1, 3, 1, 1, 2, 1, 113, 83, 49, 46, 13, 52, 4, 10, 14, 10, 3, 19, 8, 21, 151, 186, 99, 11, 29, 24, 24, 62, 15, 98, 30, 21, 63, 29, 48, 11, 16, 35, 21, 17, 6, 2, 2, 3,...

...------------------ m1 <- lmer( LogRT ~ Affix * group + (1|Subject), data= datos) pamer.fnc(m1) #---------------------------------------------------------------------------------------------------------------- # Soluciones post hoc # A) Solución uno Bonferroni # B) Solución glht # C) mcposthoc.fnc (Si no se está familiarizado no mirar. No lo he podido explicar, pues no lo entiendo) #---------------------------------------------------------------------------------------------------------------- #-------------------------------------- # A) Solución uno Bonferroni #----------------------...

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

...Dat,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 treatment in the trial, but Covariate is something that is measured posthoc and can vary in the population. I am trying to wrap my head around how to calculate a few quantities from the model and get reasonable confidence intervals for them, namely I would like to test H0: gamma=0, where gamma is the regression coefficient of the odds ratios of surviving un...

...ezANOVA(data=subset(ast.ast_coef, ast.ast_coef$coef_thr==i), dv=.(ast.values), between=.(gender), wid=.(subj), within=.(cond))} But I got the last(90th) result, not all. Here are my questions. 1) Is my command correct? 2) If correct, please let me know if I can get all 90 results. 3) What kind of postHoc would be appropriate? Thank you, Jeong [[alternative HTML version deleted]]

...data = warpbreaks) tHSD <- TukeyHSD(fm1, "tension", ordered = FALSE) $tension diff lwr upr p adj M-L -10.000000 -19.35342 -0.6465793 0.0336262 H-L -14.722222 -24.07564 -5.3688015 0.0011218 H-M -4.722222 -14.07564 4.6311985 0.4474210 I'm interested in posthoc comparisons between various levels of factor 1 and various levels of factor 2, both at the same time. I know that is possible in SPSS, but... is there any R solution? Cheers, Andrej

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' i...

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 pl...

...uals 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 punctuation after treatment 2. After this, I run a Tukey posthoc test for repeated measures as stated in gribblelab: require(nlme) a1<-lme(x~factortmnt,random=~1|factorid/factortmnt,data=mydata) print(anova(a1)) require(multcomp) summary(glht(a1,linfct=mcp(factortmnt="Tukey"))) The fact is that once I get both results, there are some occasions in...

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. -- Daniel C. Jupiter, Ph.D. Postdoctoral Research Associate Department of Systems Biology and Translational Medicine College of...

...ar 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 samples) > nmda123 Values ind 1 6.7171265 CREB 2 5.0343117 CREB 3 6.9000000 CREB 4 0.1195394 mCREB 5 0.1221876 mCREB 6 0.1900000 mCREB 7 1.0000000 No Virus 8 1.0000000 No...