similar to: Different goodness of fit tests leads to contradictory conclusions

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

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

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 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) {

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

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'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

I have been trying to produce a histogram that has two groups (male and female snakes) on the same graph (either superimposed or each frequency bar appears side by side). I found a couple of functions for superimposed histogram written by other people. The below is the codes I used for my data containing a column of svl (body size; snout-vent length) and another column of sex (male or female).

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

Frank E Harrell Jr wrote: > Eric Rescorla <ekr at rtfm.com> wrote: > >> (2) I'd like to compute goodness-of-fit statistics for my fit >> (Hosmer-Lemeshow, Pearson, etc.). I didn't see a package that >> did this. Have I missed one? > > Hosmer-Lemeshow has low power and relies on arbitrary binning of > predicted probabilities. The Hosmer-Le Cessie

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

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.

Hello, I am reaching out for a problem I have seem to hit wall on. I am trying to build a rare event model:- Default event occurred in NY/NJ area. Some key statistics: 138 default aka 4bp (.04%). Obviously my logistic and robust logistic models are failing Hosmer GOF tests and so I am thinking about bootstrapping data. I found a great read on R-help, but I was wondering if someone can help me

Hello, I was looking for a way to evaluate the goodness-of-fit of a logistic regression model. After googling, I found that I could use "resid(fit, 'gof')" method implemented in the rms package. However, since I am not used to the "le Cessie-van Houwelingen normal test statistic," I do not know which statistic from the returned from the "resid(fit,

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

Hello R experts, Is the a function to preform a Hosmer Lemshaw goodness of fit? I am running R 2.8. Thanks, AlonBen-Ari Department of Anesthesiology and CCM Univ. Pittsburgh [[alternative HTML version deleted]]

Username: BenHosmer Title: Building an RPM from Scratch Placement: http://wiki.centos.org/PackageManagement/Rpm I went through the process of building and documenting how to build an RPM from scratch using node.js as an example. I'd like to contribute this guide back to the wiki please. -------------- next part -------------- An HTML attachment was scrubbed... URL:

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

Hi, I've been running some simulations for a while and the performance of R has been great. However, I've recently changed the code to perform a sort of chi-square goodness-of-fit test. To get the observed values for each cell I've been using table() - specifically I've been using cut2 from Hmisc to divide up the range into a specified number of cells and then using