search for: mccullagh

Dear all, I've replicated the cheese tasting example on p175 of GLM's by McCullagh and Nelder. This is a 4 treatment (rows) by 9 ordinal response (cols) table. Here's my simple code: #### cheese library(MASS) options(contrasts = c("contr.treatment", "contr.poly")) y = c(0,0, 1, 7, 8,8,19, 8,1, 6,9,12,11, 7,6, 1, 0,0, 1,1, 6, 8,23,...

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I am new to generalized linear models and studying McCullagh & Nelder (1989). Especially, I have a problem resembling the \"cheese taste\" example (5.3.1. p. 109) of the book. I tried to analyse the cheese example with R but failed to do so because R allowed me to use logit link function only with binary family that supposes 0 <= y <=...

Dear all, I have a question regarding the use of stepAIC and polynomial (quadratic to be specific) terms in a binary logistic regression model. I read in McCullagh and Nelder, (1989, p 89) and as far as I remember from my statistics cources, higher-degree polynomial effects should not be included without the main effects. If I understand this correctly, following a stepwise model selection based on AIC should not lead to a model where the main effect of some...

Dear list, I'm trying to mimic the analysis of Wedderburn (1974) as cited by McCullagh and Nelder (1989) on p.328-332. This is the leaf-blotch on barley example, and the data is available in the `faraway' package. Wedderburn suggested using the variance function mu^2(1-mu)^2. This variance function isn't readily available in R's `quasi' family object, but it seems...

...lia Carvalho, we wanted to map the standardised residuals of a quasipoisson null model of cases offset by log(pop.at.risk), and rstandard.glm() seemed to compress the values more than we'd have expected. Her colleague: "Valeska (L. Andreozzi) says that she has already noticed that, and as McCullagh & Nelder (2nd ed, pg 397) says, the dispersion is inside the sqrt". (That's the way I read 12.5 on p. 397 too). I can't see that summary(model)$dispersion has already been subject to sqrt() in sum(object$weights * object$residuals^2)/df.r in summary.glm(). Should: res / (s...

Hi: Is there any function in R to fit ordinal regression models (linear and non-linear) described by Peter McCullagh. Regression Models for Ordinal Data, JRSS-B, 1980, 42:109-142 Thanks, Venkat ----------------------------------------------------------------------- E. S. Venkatraman, Ph.D. Phone: (212) 639-8520 Fax: (212) 717-3137 Assistant Attending Member Memorial Sloan-Kettering Cancer Center --...

Dear Peter. I guess you know that Jim Lindseys code include nordr and ordglm in library gnlm - I attach the htmls which do various linear and nonlinear ordinal regressions - exemplified with just the data mentioned, McCullagh (1980) JRSS B42, 109-142. I had it work very fine. -----Oprindelig meddelelse----- Fra: Peter Malewski <p.malewski at tu-bs.de> Til: Troels Ring <tring at mail1.stofanet.dk> Dato: 25. februar 2000 07:35 Emne: Re: Sv: [R] Ordinal Regression >On Thu, 24 Feb 2000, Troels Ring wrote:...

Hi R-help, Is there such a thing as a function in R for fitting a GLM where the response is distributed as a Beta distribution? In my case, the response variable is a percentage ([0,1] and continuous). The current glm() function in R doesn't include the Beta distribution. Thank you for any help on this topic. Sincerely, Sharon K?hlmann

...t somehow I can't manage to extract the probabilities from a glm.predict() result: > str(res) Named num [1:9] 0.00814 0.01877 0.025 0.02941 0.03563 ... - attr(*, "names")= chr [1:9] "1" "2" "3" "4" ... I got from: # A Gamma example, from McCullagh & Nelder (1989, pp. 300-2) clotting <- data.frame( u = c(5,10,15,20,30,40,60,80,100), lot1 = c(118,58,42,35,27,25,21,19,18), lot2 = c(69,35,26,21,18,16,13,12,12)) model <- glm(lot1 ~ log(u), data=clotting, family=Gamma) res <- predict(model, clotting) I want to transfer th...

...the confint method to calculate confidence intervals for the parameters I get the following error message Waiting for profiling to be done... Re-fitting to get Hessian Error in X[, -i, drop = FALSE] : incorrect number of dimensions Can someone explain the error-message? (The data are from McCullagh (1980), JRSS,B) tonsiles<-data.frame(carrier=factor(rep(c('yes','no'),each=3)), size=ordered(rep(c(1,2,3),2)), count=c(19,29,24,497,560,269)) library(MASS) m<-polr(size~carrier,data=tonsiles,weights=count) confint(m) Ulrich...

Two questions: 1. inverse.gaussian is up there as one of the glm families, but do people ever use it? There is no inverse.gaussian in the R distribution family, and when I checked McCullagh & Nelder, it only appeared twice in the book (according to subject index), once in the table on p. 30 and once on p. 38 in a passing sentence. Is there a good reference on this distribution? 2. When I looked at the negative binomial documentation, I couldn't quite get things match for the...

Dear Sirs, Could you please be so kind as to send us some information on residuals in multinomial logistic models? Is it possible to use R software? We thank you in advance. Sincerely yours Luciana Alves,MSc Beatriz Leimann, MD -- Luciana Correia Alves Doutoranda em Sa??de P??blica ENSP - Fiocruz

Hi all, How is dispersion calculated within the glm function in R ? Cheers _________________________________________________________________ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body",

...refer me to a textbook discussion? Two factor ANOVA repeated measures design. Each subject gives a percent correct. I am assuming the correct way to proceed is to fit a generalized linear model with binomial responses and logistic link. But I have not found a detailed discussion of this in either McCullagh & Nelder or Dobson. Here is a toy example. Each datum is proportion correct out of 100 trials for one subject: b1 b2 a1 .5,.6 .1,.2 a2 .7,.8 .2,.3 a3 .8,.9 .3,.4 (2 subjects) How does the analysis proceed? Thanks very much for any help. Bill Simpson -.-.-....

...le parameter is estimated, not really known). Are these equivalent, or approximately equivalent? Does anyone have a favorite reference on the subject? (I've been looking at V&R3, Crawley's "GLIM for Ecologists", and Lindsey's GLM book -- I haven't acquired Dobson or McCullagh and Nelder yet). -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-de...

Dear friends. Do Polr in Mass change the sign of the coefficients ? Example (McCullagh 1980) options(contrasts=c("contr.treatment","contr.poly")) library(Mass) freq <- c(19,29,24,497,560,269) yy <- ordered(gl(3,1,6)) z4 <- polr(yy~x,weights=freq) > z4 Call: polr(formula = yy ~ x, weights = freq) Coefficients: x2 -0.6026492 Intercepts:...

...in a logistic regression? It feels wrong, but I cannot find, so far, any sources on this. 2) How to implement this in R? I tried the weights option in glm(), but I think that is meant for when you have one row in your data for multiple observations, not for this kind of weight. Although I have the McCullagh and Nelder book explaining in detail how glm() operates, I cannot find a similar book for svyglm(). Is svyglm() better for this type of weighting? 3) Where would I find a good source describing the estimation procedure, including weighting, applied in svyglm()? Thanks in advance for any help! Jo...

...ve to be integers) but remember to use prior weights of 1/N and estimate the over-dispersion parameter. If you use the ratio, r, directly with a binomial total of 1 then the prior weights are simply 1 and can be ignored. This quasi-likelihood approach for a ratio was given by Wedderburn (1974) (see McCullagh and Nelder, 1989, Sec 9.2.4). BTW random effects with a beta distribution included in the linear predictor via a link function such as the logit can be fitted as a HGLM (Hierarchical Generalized Linear Model)(Lee and Nelder, 1996, 2001) for binomial data (i.e. considered binomial conditional on the...

...answer but is not the right answer. So, I am accusing my specification of the experiment (group). If you have any suggestion pleas let me know. E-mail:aleid2001 at yahoo.com Here I am going to gve mre details about the data. the > details about the data is: > > The data are: > McCullagh and Nelder (1989,sec.14.5)polished an > interesting set of data on the success of matting > between male and female salamanders drawn from two > populations, the rough butts (RB) and the white sides > (WS), that had been geographically isolated from each > other. In the first of thre...