similar to: Logistic Regression in R (SAS -like output)

Dear all, I am wondering why the step() procedure in R has the description 'Select a formula-based model by AIC'. I have been using Stata and SPSS and neither package made any reference to AIC in its stepwise procedure, and I read from an earlier R-Help post that step() is really the 'usual' way for doing stepwise (R Help post from Prof Ripley, Fri, 2 Apr 1999 05:06:03

I haven't find any helpful thread. How can i calculate BIC and Hosmer-Lemeshow statistic for a logistic regression model. I have used glm for logistic fit. -- View this message in context: http://www.nabble.com/BIC-and-Hosmer-Lemeshow-statistic-for-logistic-regression-tf3945943.html#a11193273 Sent from the R help mailing list archive at Nabble.com.

I've been using R to do logistic regresssion, and that's working well, but there are two things I haven't figured out how to do. (1) Is there some pre-existing function that will let you compute the odds ratios and confidence intervals for them for a specific fit. I know how to do this manually or even write a function that I can call with the coefficients and se, but

Dear R - help, I am working on the Credit scorecard model. I am using the Logistic regression to arrive at the regression coefficients model. I want to use the Hosmer - Lemeshow test . In order to understand the use of R - language, I had referred the following URL       http://www.stat.sc.edu/~hitchcock/diseaseoutbreakRexample704.txt The related data 'diseaseoutbreak' is available

I have a data set to be analyzed using to binary logistic regression. The data set is iin grouped form. My question is: how I can compute Hosmer-Lemeshow test and measures like sensitivity and specificity? Any suggestion will be greatly appreciated. Thank you Endy [[alternative HTML version deleted]]

I'm trying to do a Hosmer-Lemeshow 'goodness of fit' test on my logistic regression model. I found some code here: http://sas-and-r.blogspot.com/2010/09/example-87-hosmer-and-lemeshow-goodness.html The R code is above is a little complicated for me but I'm having trouble with my answer: Hosmer-Lemeshow: p=0.6163585 le Cessie and Houwelingen test (Design library): p=0.2843620

Hi, I need to calculate Kendall's tau for large data vectors (length > 100'000). Is somebody aware of a faster algorithm or package function than "cor(, method="kendall")"? There are ties in the data to be considered (Kendall's tau-b). Any suggestions? Regards Ferdinand

i want to know how to use the Hosmer?Lemeshow test? in R. Can anyone show me the program to me and tell me how to use it? -- View this message in context: http://www.nabble.com/HOW-to-use-the-Hosmer%E2%80%93Lemeshow-test%E2%80%8F-in-R-tp19675283p19675283.html Sent from the R help mailing list archive at Nabble.com.

dear all, i made some analysis with logistic regression. do you know if there is already a function available for the hosmer-lemeshow fitness test? thank you very much for the help best wishes andi

(Sorry for obvious mistakes, as I am quite a newby with no Statistics background). My question is going to be what is the gain of logistic regression over odds ratios when none of the input variables is continuous. My experiment: Outcome: ordinal scale, ``quality'' (QUA=1,2,3) Predictors: ``segment'' (SEG) and ``stress'' (STR). SEG is nominal scale with 24

Hi eveybody. I've seen posted before the same question, but no answer. Is there anybody who has implemented the Hosmer-Lemeshow test in R? TIA, Stefano -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

Hello, I can't find a package which calculates Kendall's tau-c. There is the package Kendall, but it only calcuates Kendall's tau-b. Here is the example from ttp://www2.chass.ncsu.edu/garson/pa765/assocordinal.htm. cityriots <- data.frame(citysize=c(1,1,2,2,3,3), riotsize=c(1,2,1,2,1,2), weight=c(4,2,2,3,0,4)) cityriots <- data.frame(lapply(cityriots,function(x)

Hi to everybody. I use the following routine (i found it in the internet) to compute the Hosmer-Lemeshow test in the framework of logistic regression. hosmerlemeshow = function(obj, g=10) { # first, check to see if we fed in the right kind of object stopifnot(family(obj)$family=="binomial" && family(obj)$link=="logit") y = obj$model[[1]] # the double bracket

Hello, Are there any packages/functions available for testing the assumptions underlying assumptions for a good GLM model? Like linktest in STATA and smilar. If not, could somebody please describe their work process when they check the validity of a logit/probit model? Regards, Jay

I have a data with binary response variable, repcnd (pregnant or not) and one predictor continuous variable, svl (body size) as shown below. I did Hosmer-Lemeshow test as a goodness of fit (as suggested by a kind “R-helper” previously). To test whether the predictor (svl, or body size) has significant effect on predicting whether or not a female snake is pregnant, I used the differences between

Hallo there, can anymore show me how to get results about konkordant und diskordant paars (Sommer-D, Gudman-Krustal-Gama, Kendall-Tau-a) within a logistic regression) in R? Thanks a lot. MT [[alternative HTML version deleted]]

lrm does some binning to make the calculations faster. The exact calculation is obtained by running f <- lrm(...) rcorr.cens(predict(f), DA), which results in: C Index Dxy S.D. n missing 0.96814404 0.93628809 0.03808336 32.00000000 0.00000000 uncensored Relevant Pairs Concordant Uncertain 32.00000000

Colleagues, I ran some nonparametric regressions in R (run in RedHat Linux), then a colleague repeated the analyses in SAS. When we obtained different results, I tested S-Plus (same Linux box). And, got yet different results. I replicated the results with a small dataset: DATA: 37.5 23 37.5 13 25 16 25 12 100 15 12.5 19 50 20 100 13 100 10 100 10 100 16 50 10 87.5

I know that there are two method to apply the Hosmer and Lemeshow?s. One of them is calculated based on the fixed and pre-determined cut-off points of the estimated probability of success. One of them is calculated based on the percentiles of estimated probabilities. In the previous post,i find that the Hosmer and Lemeshow?s test how to use in R. hosmerlem <- function (y, yhat, g = 10) {

Greetings, I am working on a logistic regression model in R and I am struggling with the code, as it is a relatively new program for me. In searching Google for 'logistic regression diagnostics' I came Elizabeth Brown's Lecture 14 from her Winter 2004 Biostatistics 515 course (http://courses.washington.edu/b515/l14.pdf) . I found most of the code to be very helpful, but I am