similar to: help with unequal variances

Well fellow R users, I throw myself on your mercy. Help me, the unworthy, satisfy my employer, the ungrateful. My feeble ramblings follow... I've searched R-Help, the R Website and done a GOOGLE without success for a one way ANOVA procedure to analyse data that are both non-normal in nature and which exhibit unequal variances and unequal sample sizes across the 4 treatment levels. My

Hello, I am interested in parametric multi comparison tests such as Dunnett, Duncan, Tukey, Newman-Keuls, Bonferonni, Scheffe, and non-parametric tests such as Kruskal-Wallis, and Mann-Whitney U. Are there packages that include most of these tests in each category? Many packages exist for an individual test but their outputs vary in great detail (test statistics, p-values, etc.)

Hi, All How does one remove relevant information from a regression output besides just the coefficients? I've been able to modify the example given under "help(by)" to give me some additional information, but not everything I need. If you adjust the call statement from what is listed by adding the summary statement like so: tmp <- by(warpbreaks, tension, function(x)

Hello, I'm trying to write code for a repeated measures ANOVA. To put things in perspective, I'll describe my experiment (briefly). I have a 2X2 factorial design with pH (5.5, 6.5) and local community (present, absent) as my treatments. I had plastic enclosures that I sampled across five weeks with the density of 7 species acting as my response variables. I'm analyzing one

Hi, i'm looking for an R function to fit a one-way ANOVA with one factor containing 10 levels. The factor levels have different numbers of observations (varying between 20 to 40). For most of the dependent variables i'm testing there are unequal variances among the factor levels. I see the function oneway.test: oneway.test(variable ~ factor, data=dataset) which by default does not

Hello all, Here goes one of my first functions. I want to make a nonparametric multiple sample comparison with unequal sample sizes (see Zar?s Biostatistical Analysis, 3rd. Ed., pg. 201 Example 10.11, pg. 288 Example 11.10). In the real world, I want to compare samples of fish length captured with different fishing gears. After using the Kruskal-Wallis test I want to check the differences

How does one implement a likelihood-ratio test, to test whether the variances of the random effects differ between two groups of subjects? Suppose your data consist of repeated measures on subjects belonging to two groups, say boys and girls, and you are fitting a linear mixed-effects model for the response as a function of time. The within-subject errors (residuals) have the same variance in

Hello - I am fairly new to R, (i.e., ability to create functions/write programs insignificant) and was wondering if there might be a convenient way to model the following: I want to fit a gaussian glm to grouped data, while allowing for unequal variances in each of the groups. More specifically, my data set looks something like this: ---------------- data group 1 76 1 2 82 1 3

Hello- I have run an ANOVA on 4 treatments with unequal sample sizes (n=9,7,10 and 10). I want to determine where my sig. differences are between treatments using a Bonferroni test, and have run the code: pairwise.t.test(Wk16, Treatment, p.adf="bonf") I receive an error message stating that my arguments are of unequal length: Error in tapply(x, g, mean, na.rm = TRUE) :

Dear Douglas and R-help, Does lme assume normal distribution AND equal variance among groups like anova() does? If it does, is there any method like unequal variance T-test (Welch T) in lme when each group has unequal variance in my data? Thanks, Shirley

This is in followup to a thread on R-help with subject "Sampling". I claim that R does the wrong thing by default when sampling with unequal probabilities without replacement - the selection probabilities are not proportional to 'prob', for any draw after the first: I suggest that R do what S-PLUS now does (though you're free to choose a better implementation). What S-PLUS

Dear R-wizards! I have been learning on my own how to use this fantastic program.. but I agree with some people that even with the manuals, the faq and so on.. when you are sitting fully alone.. progress can be ... slow... very slow indeed.. In fact sometimes, looking at the "solutions" provided by some of you- I am just flabbergasted to the point that I couldn't figure out how to

Without recycling you would get: u <- c(10, 20, 30) u + 1 #[1] 11 20 30 which would be pretty inconvenient. (Note that the recycling rule has to make a special case for when one argument has length zero - the output then has length zero as well.) Bill Dunlap TIBCO Software wdunlap tibco.com On Tue, Dec 12, 2017 at 9:41 PM, Maingo via R-help <r-help at r-project.org> wrote:

Hi, I am doing multiple regression, and have several X variables that are categorical. I read that I can use dummy or contrast codes for that, but are there any special rules when there're unequal #observations in each groups (4 females vs 7 males in a "gender" variable)? Also, can R generate these codes for me? THanks.

I am using levelplot() from lattice with grids that have unequal cell sizes. This means that the boundary between two cells is not always half-way between nodes, as levelplot() assumes. The result is that some cell sizes are rendered incorrectly, which can be painfully obvious if using relatively large cells. Is there any work-around? I am using the conditioning capability of lattice and

Dear R users, I need to merge two data frames based on both equal and unequal comparisons. The "sqldf" package used to work well , but today, I cannot resolve the following error by reinstallation of the sqldf package. Can anyone suggest a different way to perform this kind of merge function? Thank you, Ding > DMRlog2pbde47DMS <- sqldf("select * from DMR_log2pbde47 as a

Hello, I?ve tried several times to learn R, but have never gotten past a particular gate. My data are organized by column in Excel, with column headers in the first row. The columns are of unequal lengths. I export them as CSV, then import the CSV file into R. I wish to summarize the data by column. R inserts NA for missing values, then refuses to operate on columns with NA. R is importing

Hello All, Would anyone be able to help me understand how R computes a quantile-quantile plot for comparing two data samples with unequal sample sizes? Normally, the procedure should be to rearrange the larger data sample into n equally-spaced parts using interpolation, where n is the sample size of the smaller sample, and then plot the matching data pairs. I tried using different plotting

Hi, I am having problems getting cohen's kappa to work. I have been using the function: ><-ckappa(x,y) from the psy package. I am trying to test for inter-observer reliability, I have 2 observers and 26 categories, however, the two observers might not necessarily have the same range of categories (I have unequal score ranges). However, I thought R could cope with this. Each time I

I am getting a repeated error when I try to run a logistic regression in R 2.8.1 >(glm(prop1~x1,data=glm1,family=binomial("logit"),weights=nt1)) Error in model.frame.default(formula = prop1 ~ x1, data = glm1, weights = nt1, : invalid type (list) for variable 'x1' x1 is multistate categorical (3 categories). 2 of the categories have 12 observation, one has 9. Is this what