similar to: Hosmer Lemshaw

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) {

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.

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.

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

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 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

the package of R which is related Hosmer?Lemeshow test? -- View this message in context: http://www.nabble.com/the-package-of-R-which-is-related-Hosmer-Lemeshow-test--tp19613179p19613179.html Sent from the R help mailing list archive at Nabble.com.

Dear All, I am looking for function's code to implement the Hosmer-Lemeshow gof test for survival data. Could anyone share it? TIA Mario [[alternative HTML version deleted]]

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

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

This is a question of clarification. IN 2009 Higgins, Thompson and Spiegelhalter (J R Statist Soc A 172:137-159) gave WinBUGs code to get credible intervals from random effects meta analysis for the prediction interval of a new study. It appears that the predict.rma function creates approximate credible intervals (pending a function revision by the author) for that purpose. Is my assumption

In the non linear mixed effects package a groupedData object can be created to facilitate modeling. The gD object includes a formula of the form 'response variable' ~ 'primary covariate' | 'grouping factor'. In experiments creating response surfaces there are 2 or more primary covariates. Is there any way to use the groupedData() function to include 2 primary

Dear R Masters, I'm an anesthesiology resident trying to make his way through basic statistics. Recently I have been confronted with longitudinal data in a treatment vs. control analysis. My dataframe is in the form of: subj | group | baseline | time | outcome (long) or subj | group | baseline | time1 |...| time6 | (wide) The measured variable is a continuous one. The null hypothesis in

Hi, I using the boot package 1.2-20 on R 2.0.1. My statistics function estimates 6 parameters. In a small percentage of resampled data sets my statistics function doesn't produce an estimate for one parameter and the boot function stops with an error. I can write an ifelse(exists('parameter.estimate'), parameter.estimate, NA) statement within the statistic function to substitute

Hi All, I'm new at programming in R. Some functions create objects for which extractor functions are written to pull out some partial result. I wish to extract partial results from functions without extractor functions: for example, to pass a vector of results to another function. Even after looking at V&R S Programming I don't see a general approach. Specifically, how would I

> Hello, > > I'm running R 1.8.1 on a Mac G4 with Dual 800 MHz CPU, 1.5 GB RAM, and > sufficient disk space. > > I have loaded the boot package version 1.2-15. > > I defined a function to pass to the statistic argument which estimates > a vector (length = 6) of parameter estimates; none are variances. > > I defined a function to pass to the ran.gen argument

Running under Redhat 7.3 Linux I have installed R Version 1.8.0 (2003-10-08) from a binary download using the rpm manager. Using packageStatus(), I am attempted to upgrade several packages. This is unsuccessful with the following error messages: * Installing *source* package 'MASS' ... ** libs gcc -I/usr/lib/R/include -I/usr/local/include -D__NO_MATH_INLINES -mieee-fp -fPIC -O2

Hello, I have openSUSE 11.1 Trying to install randomForest as SU after invoking R install.packages("randomForest") and I get this * Installing *source* package ‘randomForest’ ... ** libs gcc -std=gnu99 -I/usr/lib/R/include -I/usr/local/include -fpic -O2 -c classTree.c -o classTree.o gcc -std=gnu99 -I/usr/lib/R/include -I/usr/local/include -fpic -O2 -c regTree.c -o

I am trying to test goodness of fit for my legalistic regression using several options as shown below.  Hosmer-Lemeshow test (whose function I borrowed from a previous post), Hosmer–le Cessie omnibus lack of fit test (also borrowed from a previous post), Pearson chi-square test, and deviance test.  All the tests, except the deviance tests, produced p-values well above 0.05.  Would anyone please

I am having trouble compiling R-1.1.0 on a Sun Ultra 60 machine running Solaris 7. Suggestions are greatly appreciated. I modified the CPPFLAGS and LIBS variables in the config.site file. As far as I can tell, I have included all the non-standard headers and libraries installed on my Sun station. My GNU stuff is installed in /opt/Summertime_98.sparc/, and at the bottom of this message I