similar to: post-hoc after ancova

Hello, Despite my search, I didn't find a post-hoc test for an ANCOVA. I used the functions aov() and lm() to run the ANCOVA then I tried TukeyHSD() but it didn't work (because of the covariable is a continuous variable?). Furthermore, I would like to plot the adjusted values (i.e. the values of the tested variable taking into account the covariable). Thanks for your help! N. Poulet

Dear R-helpers, I have an ANCOVA with a significant effect of the factor, which has three levels. I wish to determine which of the levels are different from each other but, because my model was fitted with lm(), I cannot use TukeyHSD. For some reason, I get different results (no significant effect of the factor) when I fit the model using aov() so, for the moment, I am using lm(). Could anyone

Dear R Users, Recently I began to use R. I`m interested about comparing several regression curves. REcently I found the package sm and the function sm.ancova which I understand allows me to do this. I applied this function to my data (seven regression curves) and I found that there are significant differences. Nevertheless, when I want to find out where are the differences, the package tells that

Could you please help me on the following ANCOVA issue? This is a part of my dataset: sampling dist h 1 wi 200 0.8687212 2 wi 200 0.8812909 3 wi 200 0.8267464 4 wi 0 0.8554508 5 wi 0 0.9506721 6 wi 0 0.8112781 7 wi 400 0.8687212 8 wi 400 0.8414646 9 wi 400 0.7601675 10 wi 900 0.6577048 11 wi 900

I am looking for the R install package. Any leads to sites from where I can download the same? Thanks Robert ===== Robert John Graduate Student Centre for Ecological Sciences Indian Institute of Science Bangalore 560 012 INDIA Phone : 91-80-3600985 91-80-3092506 Fax : 91-80-3601428 e-mail : robert at ces.iisc.ernet.in

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

Hi list, does anybody know a easy to understand example in R which shows how to perfom an ANCOVA? I already tried to understand the example which you get when you type ?aov, but I did not really understand the output. Best, syrvn -- View this message in context: http://n4.nabble.com/R-example-for-ancova-tp949324p949324.html Sent from the R help mailing list archive at Nabble.com.

Hallo! Does anyone know a possibility to perform a sample size estimation for an ANCOVA? Would be great! Thanks Karl

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'm puzzled cause when i did anova with the help of R and StatView, i didn't get same results ! Indeed, the model is aov(Vol~apoe*hta*Age) where ope and hta are 2 levels factor, and Age is quantitativ data. We observed same results concerning : Residual interaction apoe:hta:Age and other outputs are different. Does anyone have an idea ? -- Delcroix Nicolas - GIN -

Hi all, I am trying to fit an ANOVA model in R using the aov/lm commands. I have a set of observational (i.e. no fixed experimental effects) data, in which I have identified high and low clusters of the response variable. The design is unbalanced, with 773 high cluster observations, and 523 low cluster observations. I would like to test a set of 7 correlates to see if there are significant

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

How to Ancova in R? I know this has got to be an FAQ, because I see it asked in the lists, but I haven't seen an answer to it. I see the R-sm has the ancova thing happening, but I kind of doubt that what I'm trying to do is "smoothing"... -- Pete Hurd phurd at uts.cc.utexas.edu http://www.zo.utexas.edu/research/phurd Section of Integrative Biology, University of Texas, Austin

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 =

I would like to know if there is a way of directly calculating the F-ratio of a random effect using the "aov" function. I have 2 factors in my model, "population" which is random and "length" which is the length of female fish within each population. The dependent variable is "diam" which is the average diameter of eggs produced by each female. At

Dear R-users, is there a chance to do an nested ANCOVA in R? I've read the archive mails but it doesn't work. We have the following situation: We are interested in differences in carabid biomass at different aged woodlands. Thus, we have a nested design with 2 fixed groups (0=recent, 1=ancient) and 10 woodlands (each with 8 replications/traps) per fixed group. Woodland is therfore

Hi, I have a microarray data which has about 10000 genes and 15 measurements. The 15 measurements contain 6 control, 3 low dose, 3 medium dose, 3 high dose. If I treat the dose level as a continuous variable, how can I use ANCOVA to do gene selection? (I mean to select those genes that response to different level of doses differently?). Thank you very much! James

Dear all, I would like to know how to run an analysis of covariance in R. For example, I have a data frame ("data") consisting of two second-degree categorical variables ("diagnosis" and "gender"), one continous independent variable ("age") and one continous dependent variable ("response"). I ran a simple anova to see the effects of diagnosis

Dear All, I wonder if anyone has written a code for power analysis with repeated measures ANCOVA? I am aware of the following reference: Frison L and Pocock SJ: Repeated Measures in Clinical Trials: analysis using mean summary statistics and its implications for design in Statistics in Medicine, 1992, 11:1685-1704. Statistics in Medicine It will probably be fairly easy to code this up

Dear list members: I searched the R-help for packages to calculate power for an ANCOVA problem I have. I have found power.t.test, power.anova.test. But it seems that I can not found one with ANCOVA. I have two datasetsets with variables: univariate response(one data with continous response and one with 0 and 1), treatment(two levels), covariates(x1,x2,x3). I would appreciate your help. Tony