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...My question: do I need to use a numerical coding scheme for the categorical variables as required by some statistical software packages, with some sort of numeric dummy-variable coding? I am using: glm(binvar~x+y+z, family=binomial(link="logit")) Thanks, Ravi Kulkarni -- View this message in context: http://n4.nabble.com/Coding-of-categorical-variables-for-logistic-regression-tp1694250p1694250.html Sent from the R help mailing list archive at Nabble.com.

I am trying to reproduce the output of a time series example in Koop's book "Analysis of Financial Data". Koop does the example in Excel and I used the ts function followed by the lm function. I am unable to get the exact coefficients that Koop gives - my coefficients are slightly different. After loading the data file and attaching the frame, my code reads: > y = ts(m.cap) >

I have tried looking for the source code for the pt() function in https://svn.r-project.org/R/trunk/src/library/stats/ and am unable to find it there. Can someone please tell me where to find it? Thanks, Ravi Kulkarni -- View this message in context: http://n4.nabble.com/Source-code-for-the-t-distribution-tp1585875p1585875.html Sent from the R help mailing list archive at Nabble.com.

...actor). An ANOVA done using: > aov(score~factor(group), data=mydata) gives the right answers. But > aov(score~group, data=mydata) also produces an ANOVA table, with incorrect entries. My question is: what exactly is R doing when I did not specify that "group" was a factor? Ravi Kulkarni -- View this message in context: http://r.789695.n4.nabble.com/Question-about-factor-that-is-numeric-in-aov-tp2164393p2164393.html Sent from the R help mailing list archive at Nabble.com.

I know this is a very elementary question... I could not find a solution looking at old posts. I am unable to access a variable outside the scope of a for loop, even when the variable was defined before the loop: haar <- function() { a = c(1.4560773, 2.3752412, 0.9798882, 3.0909252, 2.3986487, 1.8581543) for (i in c(1:100)) { m = matrix(rnorm(36)+1i*rnorm(36),6) qrm = qr(m) Q = qr.Q(qrm)

Hello, I believe the aov() function in R uses a "Type-I sum-of-squares" by default as against "Type-III". This is relevant for me because I am trying to understand ANOVA in R using my knowledge of ANOVA in SPSS. I can only reproduce the results of an ANOVA done using R through SPSS if I specify that SPSS uses a Type-I sum-of-squares. (And yes, I know that when the sample

Hello, I notice that when I do Levene's test to test equality of variances across levels of a factor, I get different answers in R and SPSS 16. e.g.: For the chickwts data, in R, levene.test(weight, feed) gives F=0.7493, p=0.5896. SPSS 16 gives F=0.987, p=0.432 Why this difference? Which one should I believe? (I would like to believe R :) Ravi -- View this message in context:

I know this is not really an R question - it is a query about a recent book on R ("R In Action") by Robert Kabacoff, (Manning Publications 2011). There are many references to interesting topics in R in the book, BUT, I do not find a bibliography/list of references in the book! Does anybody know if there are errata for the book available some place? Thanks, Ravi -- View this message

I am trying to work out a bootstrapped Tobit regression model. I get the coefficients all right, but they all have standard error zero. And I am unable to figure out why. I know the coefficients are correct because that's what I get when do a Tobit (without bootstrapping). Here's my code: # Bootstrap 95% CI for Tobit regression coefficients? library(boot) library(AER) # for the Affairs

...ression model and in what order. Is this what the various "Types" of ANOVA correspond to? I mean that I think of my ANOVA as a regression model (a General Linear Model) and the various ways of entering predictors as the various ANOVA "Types". Hope that makes sense... Ravi Kulkarni -- View this message in context: http://n4.nabble.com/ANOVA-Types-and-Regression-models-the-same-tp1574654p1574654.html Sent from the R help mailing list archive at Nabble.com.