similar to: can I add line breaks to the paste() function?

Hello Prof. Harrell and dear R-help mailing list, I wish to perform a non-parametric repeated measures anova. If what I read online is true, this could be achieved using a mixed Ordinal Regression model (a.k.a: Proportional Odds Model). I found two packages that seems relevant, but couldn't find any vignette on the subject: http://cran.r-project.org/web/packages/repolr/

Hi, I would like to write a function that finds parameters of a log-normal distribution with a 1-alpha CI of (x_lcl, x_ucl): However, I don't know how to optimize for the two unknown parameters. Here is my unsuccessful attempt to find a lognormal distribution with a 90%CI of 1,20: prior <- function(x_lcl, x_ucl, alpha, mean, var) { a <- (plnorm(x_lcl, mean, var) - (alpha/2))^2 b

Hi All, I'm trying to use R2wd to send a dataframe to Word. The dataframe isn't huge - 300 rows, 12 variables, although it has some long strings in it. Using: wdTable(format(myDataFrame)) or wdTable(myDataFrame) Produces a very complex table, which Word struggles to process and layout. (I can't work out what the table is - it seems to be nested tables. Converting to text gives

Hi All, I was wondering if anyone knew of a function which would generate data from a pre-specified correlation matrix (as in the Stata command r2corr) or sampled from a population with a specific covariance/correlation. (I thought I'd check before I wrote something inelegant and slow.) Jeremy -- Jeremy Miles Psychology Research Methods Wiki: www.researchmethodsinpsychology.com

I guess my subject says it all. But I loaded a dataset in spss and used the foreign package to read and save it in R. Running an anova (using the aov command) gives a different F and p value in R than it does in SPSS. ANy idea what is going on? -- View this message in context: http://n4.nabble.com/R-ANOVA-gives-diferent-results-than-SPSS-tp1477322p1477322.html Sent from the R help mailing list

Dear List, does anyone know how I can test the strength of a correlation? Cheers, Anna

Dear Sir or Madam, I am trying to explore the citation bias by perfroming meta-analysis. I need to plot a forest plot on some other proportions other than the usual effect size OR,RR, RD. I still do not have any idea after searching google and reading relevant books. Can anyone kindly help? Thank you in advance. Best wishes weiwei [[alternative HTML version deleted]]

Dear R users, I am wondering about the following results: > p.adjust(c(0.05,0.05,0.05),"fdr") [1] 0.05 0.05 0.05 > p.adjust(c(0.05,0.04,0.03),"fdr") [1] 0.05 0.05 0.05 Why does p.adjust(..., "fdr") not adjust p-values, if they are constant? Does somebody have an explanation or can point to a reference? Thanks in advance, Will

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Hello, I am trying to write math-type on a plot. Due to space limitations on the plot, I want 2 short expressions written on top of each other. It is certainly possible to write them in two separate calls, but that involves fine-tuning locations and a lot of trial and error (and I'm trying to write a general purpose function). Here's where I've gotten to:

Hi, If a matrix is not positive definite, make.positive.definite() function in corpcor library finds the nearest positive definite matrix by the method proposed by Higham (1988). However, when I deal with correlation matrices whose diagonals have to be 1 by definition, how do I do it? The above-mentioned function seem to mess up the diagonal entries. [I haven't seen this complication, but

Dear all, I am looking for some interactive study materials on Principal component analysis. Basically I would like to know what we are actually doing with PCA? What is happening within the dataset at the time of doing PCA. Probably a 3-dimensional interactive explanation would be best for me. I have gone through some online materials specially Wikipedia etc, however what I need a "movable

Hi R-colleagues. In the sem-package i have a problem to introduce hidden variables. As a simple example I take an ordinary factor analysis. The program: cmat=c(0.14855886, 0.05774635, 0.08003300, 0.04900990, 0.05774635, 0.18042029, 0.11213013, 0.03752475, 0.08003300, 0.11213013, 0.24646337, 0.03609901, 0.04900990, 0.03752475, 0.03609901, 0.31702970)

I am a new user of the function sem in package sem and lavaan for structural equation modeling 1. I don?t know what is the difference between this function and CFA function, I know that cfa for confirmatory analysis but I don?t know what is the difference between confirmatory analysis and structural equation modeling in the package lavaan. 2. I have data that I want to analyse but I have some

My interpretation of the relation between 1-way ANOVA and Wilcoxon's test (wilcox.test() in R) is the following. 1-way ANOVA is to test if two or multiple distributions are the same, assuming all the distributions are normal and have equal variances. Wilcoxon's test is to test two distributions are the same without assuming what their distributions are. In this sense, I'm wondering

Hi all, I have a server which is really difficult to restart because of usage requirements and the fact that it's in a co-lo rack so miles away. I've added a couple of drives which I'd like to bring up and add to LVM but the config I know is in the PERC BIOS and requires a reboot. Can the config be changed in the openmanage suite and if so can someone point me in the right

Hello, I'm new to R and have been following many guides including the two-way anova (http://www.personality-project.org/r/r.anova.html). Using that walkthrough including the supplied data I do str(data.ex2) and receive the appropriate types of data as follows: > str(data.ex2) 'data.frame': 16 obs. of 4 variables: $ Observation: int 1 2 3 4 5 6 7 8 9 10 ... $ Gender :

Hi, I need some opinion.  I would like to use graph that I generate from R code and save it into word document.  Which format is better? pdf, jpeg or tiff? Thank you. [[alternative HTML version deleted]]

Hello, I am interested in finding the quantile of the mean of a vector, something analogous to using the pnorm(), but for an mcmc chain instead of a distribution with known parameters. One approach would be to write a function that finds the index of x_i that minimizes (x-mean(x))^2 I suspect there is a function available to do this, but I can't find it? Thank you, David