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...s suggested in the help file. The fpca function (PCA plot with pvalues and compatible with dependant/independant variables dichotomy) has been extended. As usual, any kind of feedback is the most welcome Bruno ------------------------------------------------------------------------ Bruno Falissard Dpartement de sant publique Hpital Paul Brousse 14 Avenue Paul Vaillant Couturier 94804 Villejuif cedex, France tel : (+33) 6 81 82 70 76 fax : (+33) 1 45 59 34 18 web site : <http://perso.wanadoo.fr/bruno.falissard/> http://perso.wanadoo.fr/bruno.falissard/ -------------------------...

...s suggested in the help file. The fpca function (PCA plot with pvalues and compatible with dependant/independant variables dichotomy) has been extended. As usual, any kind of feedback is the most welcome Bruno ------------------------------------------------------------------------ Bruno Falissard Dpartement de sant publique Hpital Paul Brousse 14 Avenue Paul Vaillant Couturier 94804 Villejuif cedex, France tel : (+33) 6 81 82 70 76 fax : (+33) 1 45 59 34 18 web site : <http://perso.wanadoo.fr/bruno.falissard/> http://perso.wanadoo.fr/bruno.falissard/ -------------------------...

Dears, I'm a college student and In doing my statistics homework. I use R with SEM package as my tool for sem analysis, but my teacher told me AMOS is more suitable for such analysis. Could someone help tell me whether it is true that some commercial software is better accepted in academic fields? Sorry if I should not post such topics here. -- Best Regards, Reeyarn T. Lee Accounting

Hi again Sorry, in looking again at sammon and isoMDS I see that they seem to do exactly what I want, except that they are non-metric, which means, as I understand it, that they relate the rank orders of the variables rather than the actual distances. Could I use these non-metric MDS packages even if my distances are metric? Thanks Karen -- Karen Kotschy Centre for Water in the Environment

Hello, I have climatic data of various years with many missing values. I would like to know what tools in R are most suited to estimate this missing values. (New in R and quite new on statistics). Thanks, G

Hi all, I have relatively small dataset on which I would like to perform a PCA. I am interested about a package that would also combine a method for determining the number of components (I know there are plenty of approaches to this problem). Any suggestions about a package/function? thanks, Nick -- View this message in context:

Hi. I have data which i would want to assess the degree of agreement between two assays, e.g., to evaluate reproducibility or for inter-rater reliability. I have used the Pearson product-moment correlation coefficient. It looks good ranginging between 0.90 to 0.998. Though this looks good. I am told the Concordance correlation coefficient will give a better picture of how reproducible the assay

I'm in this situation: factorlabels <- c("School", "College", "Beyond") with data for 8 families: education.man <- c(1,2,1,2,1,2,1,2) # Note : no "3" values education.wife <- c(1,2,3,1,2,3,1,2) # 1,2,3 are all present. My goal is to create this table: School College Beyond

I work for a Investment group with a very extensive training program and we are having our new hires take a statistics course at University of Chicago where they have to complete some assignments with R. I was wondering if there are any online tutorials that exist where we could get our participants comfortable with R before the class itself? I appreciate any help at all. Thanks, Matt Maxon

Are there functions available computing the gamma-correlation for ordinal scaled variables and kappa-accuracy for nominal variables, thanks, Mark ........................................................................... Swiss Federal Institute for Forest, Snow and Landscape Research Zuercherstrasse 111 - 8903 Birmensdorf - Switzerland e-mail: markus.schwarz at wsl.ch www:

...have never used R, the book begins with a self-contained introduction to R that lays the foundation for later chapters. Discounted Price: $63.96 / £39.99 For more details and to order: http://www.crcpress.com/product/isbn/9781439873656 **** Analysis of Questionnaire Data with R Bruno Falissard, INSERM U669, Paris, France ISBN: 9781439817667 Publication Date: September 2011 Number of Pages: 280 Analysis of Questionnaire Data with R translates certain classic research questions into statistical formulations. As indicated in the title, the syntax of these statistical formulati...