similar to: Power analysis

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

Hello All, I posted a similar question before, but the direction was driven to whether my case is suitable for a wilcoxon test. After research about the appropriateness, I am pretty sure that a wilcoxon test is the right tool for my case. But how to compute the power of the test is still an unanswered question bothering me. The basic stats of my two paired samples are: mean1 = 0.0032, sd1 =

Hi, I am trying to write R code to produce a power curve to show how the power of a Wilcoxon-test varies depending on the mean, with data generated from a uniform distribution. Any ideas how I should go about this?Louisa _________________________________________________________________ Amazing prizes every hour with Live Search Big Snap [[alternative HTML version deleted]]

Hi list members Any easy way to get standardized cronbach's alpha for a scale, as in SPSS? Thanks Steve Powell proMENTE social research research | evaluation | training & consulting Kranj?evi?eva 35, 71000 Sarajevo mobile: +387 61 215 997 | office: +387 33 556 865 | fax: +387 33 556 866 Checked by AVG Free Edition. 17:44

hie 1...i'm trying to carryout a relibility testusing cronbach's alpha what fuctin do i use. 2.. this is more of a statistical question.if the alpha value for all the variables is negative what does it mean. and if the alpha value is negative for all tyha variables but is greater than 0.7 for some sections of the variables what does that mean thanks in advance

Hello, I am hoping someone could shed some light on power calculations for me. I have two small data sets of unequal sample size after NA removal (m = 5, f = 7). m <- c(2.0863, 2.1340, 2.1008, 1.9565, 2.0413, NA, NA) f <- c(1.8938, 1.9709, 1.8613, 2.0836, 1.9485, 2.0630, 1.9143) In a R help message/reply from Sep 30, 2001, it was noted that the "power.t.test" function

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",

I am taking a behavioral stats graduate class and the instructor is using SPSS. I'm trying to follow along in R. Recently in class we started working with scales and survey data, computing Cronbach's Alpha, reversing values for reverse coded items, etc. Also, SPSS has some built in functionality for entering the meta-data for your survey, e.g. the possible values for items, the text of

Does anyone know how can I calculate power in wilcoxon.test, kruskal. test and oneway.test in an F? I have already found power.t.test for calculating power in t.test but it seems that there is nothing for the others. Any answer could be useful. Thanks for your interest. --------------------------------- [[alternative HTML version deleted]]

Dear Listers: I used cronbach{psy} to evaluate the internal consistency and some set of variables gave me alpha=-1.1003, while other, alpha=-0.2; alpha=0.89; and so on. I am interested in knowing how to interpret 1. negative value 2. negative value less than -1. I also want to re-mention my previous question about how to evaluate the consistency of a set of variables and about the total

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 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 have run the following logistic regression model: options(contrasts=c("contr.treatment", "contr.poly")) m <- glm(wolf.cross ~ null.cross + feature, family = "binomial") where: wolf.cross = likelihood of wolves crossing a linear feature null.cross = proportion of random paths that crossed a linear feature feature = CATEGORY of linear feature with 5 levels:

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 users, I would like to know if there is a way in R to execute a post-hoc test (factor levels comparison, like Tukey for ANOVA) of a non-parametric analysis of variance with kruskal.test() function. I am comparing three different groups. The preliminary analysis using the kruskal-wallis-test show significance, but I still don''t know the relationship and the significance level

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

Hi, What package would you recommend for analyzing the validity/reliability of multiple choice tests. Doing things such as classical test analysis, factor analysis, item response theory. I've used psychometric (item.exam), MiscPsycho (alpha.Summary), and ltm (rcor.test). MiscPsycho reported the numbers most similar to what I get in SPSS: corrected point biserial correlations,

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

how do I check the rank of a matrix ? say A= 1 0 0 0 1 0 then rank(A)=2 what is this function? thanks I did try help.search("rank"), but all the returned help information seem irrelevant to what I want. I would like to know how people search for help information like this. rank(base) Sample Ranks SignRank(stats) Distribution of the