Re: [R] A Quick and (Very) Dirty Intro to Stats in R
John, Your appendix on linear mixed models does look good and I look forward to reading it, but its 24 pages and Jarretts entire guide is less than 8 pages, so my simple I think he meant short! Thanks, Roger On 11/8/05, John Fox [EMAIL PROTECTED] wrote: Dear Jarrett, -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Jarrett Byrnes Sent: Tuesday, November 08, 2005 6:41 PM To: R-help@stat.math.ethz.ch Subject: [R] A Quick and (Very) Dirty Intro to Stats in R . . . Most importantly, there are still a few holes that need to be filled - if they can be 1) A SIMPLE explanation for how to do mixed models using lme. I am quite unsatisfied with most of what I've seen on the net, and if it even comes close to going over my head, it really won't fly with most folk I know. I've done the best I can, but I know if falls short. Possibly take a look at the appendix on mixed models to my R and S-PLUS Companion to Applied Regression, available at http://socserv.socsci.mcmaster.ca/jfox/Books/Companion/appendix-mixed-model s.pdf. This was intended to be a simple explanation. Regards, John __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] A Quick and (Very) Dirty Intro to Stats in R
Greetings to all, First off, I want to thank you all for answering any nagging questions I've had over the past few days. I've been in the process of putting together A Quick and (Very) Dirty Intro to Doing Your Statistics in R (which I have posted to http://didemnid.ucdavis.edu/rtutorial.html ) in order to teach an R workshop for the graduate students in my department. This is a guide for your everyday stats crunchers who want to free themselves from the cycle of SAS updates, have more flexibility than JMP or Statview will allow, but are not hardcore programming/think-about-stats-allday types. These are people who get data from the natural world, and then find out what it's telling them. So, to that end, I've put the guide together, and would be very interested in any comments you all would have. Are there any statistical methods that you think I really should have included for this type of audience that I didn't (and if it's over my head, would you be interested in contributing)? Is there anything just blatantly wrong or is unclear to a casual reader? Most importantly, there are still a few holes that need to be filled - if they can be 1) A SIMPLE explanation for how to do mixed models using lme. I am quite unsatisfied with most of what I've seen on the net, and if it even comes close to going over my head, it really won't fly with most folk I know. I've done the best I can, but I know if falls short. 2) A method of looking at type II and III sums of squares for aov if there is a different error term included. 3) How does one plot canonical values and centroid groupings for a MANOVA? 4) How does one use manova to do repeated measures? I've got the univariate method down, but would like to use manova a la the repeated statement in SAS. 5) Better output for post-hocs, and a Ryan's Q implementation. Thanks in advance for any input, and I hope this can be a resource to a lot of people! Jarrett Byrnes Population Biology Graduate Group, UC Davis Bodega Marine Lab 707-875-1969 http://www-eve.ucdavis.edu/stachowicz/byrnes.shtml __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] A Quick and (Very) Dirty Intro to Stats in R
Jarrett Byrnes [EMAIL PROTECTED] writes: 4) How does one use manova to do repeated measures? I've got the univariate method down, but would like to use manova a la the repeated statement in SAS. The examples for anova.mlm should detail this rather explicitly. -- O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] A Quick and (Very) Dirty Intro to Stats in R
Dear Jarrett, -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Jarrett Byrnes Sent: Tuesday, November 08, 2005 6:41 PM To: R-help@stat.math.ethz.ch Subject: [R] A Quick and (Very) Dirty Intro to Stats in R . . . Most importantly, there are still a few holes that need to be filled - if they can be 1) A SIMPLE explanation for how to do mixed models using lme. I am quite unsatisfied with most of what I've seen on the net, and if it even comes close to going over my head, it really won't fly with most folk I know. I've done the best I can, but I know if falls short. Possibly take a look at the appendix on mixed models to my R and S-PLUS Companion to Applied Regression, available at http://socserv.socsci.mcmaster.ca/jfox/Books/Companion/appendix-mixed-model s.pdf. This was intended to be a simple explanation. Regards, John __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
