similar to: Generalized Estimating Equations and log-likelihood calculation

Hello, Is it possible to derive Pan's QIC (2001 Biometrics 57:120) from either a fitted gee() object in the gee package or from a geese() fit in the geepack package? If so, would anyone be kind enough to provide me with code to do so? I realize that QIC is part of the output from yags() but I would like to use one of the other functions. Thanks. Richard

Dear all, Using the quasibinomial and quasipoisson families results in no AIC being calculated. However, a quasi AIC has actually been defined by Lebreton et al (1992). In the (in my opinon, at least) very interesting book by Burnham and Anderson (1998,2002) this QAIC (and also QAICc) is covered. Maybe this is something that could be implemented in R. Take a look at page 23 in this pdf:

Hello, I built the entire Vorbis kit on my PowerMac G4 running OSX 10.4.6. I'm having problems however doing anything with the libao package. Any time I try to use the library to link it errors out with the following message: /usr/bin/ld: Undefined symbols: _dlsym_auto_underscore collect2: ld returned 1 exit status If I try to run the ogg123 application I get this:

Hi, I'm using 'geepack' to run Generalized Estimating Equations. I'm aware that I can use anova to compare two models, but would it be possible to test QIC on R? It seems that there were similar questions a couple of years ago, but the question has not been answered yet. I'd appreciate if someone could show me the code! Thank you, Sachi [[alternative HTML version

I'm using the package geepack to fit GEE models. Does anyone know of methods for add1 and drop1 for a 'geeglm' model object, or perhaps a method for extractAIC based on the QIC of Pan 2001? I see there has been some mention of this on R-help a few years ago (RSiteSearch("QIC")). The package does provide an anova method for its model objects, and update() seems to work:

I installed fink and now I have the /sw/lib, however that didn't fix my problem. I went as far as to take out the - Ddlsym=dlsym_auto_underscore out of the configuration files. Now however the libao package won't build at all and yips about this: [ukiel:/MP3/OGG/libao-0.8.6] wind% make Making all in src Making all in plugins Making all in oss make[3]: Nothing to be done for

Dear R users I am analysing data from a group of twins and their siblings. The measures that we are interested in are all correlated within families, with the correlations being stronger between twins than between non-twin siblings. The measures are all calculated from survey answers and by definition have limited ranges (e.g. -5 to +5), though within the range they are approximately normally

Hello Everybody: I am searching for an R package for fitting Generalized Estimating Equations (GEE) with weights (i.e. Weighted Estimating Equations). From the R documentation I found "geese(geepack)" for fitting Generalized Estimating Equations. In this documentation, under the paragraph “weights” it has been written, “an optional vector of weights to be used in the fitting process.

This is what there is in winbindd_idmap.tdb of both members that i have, whewre file server 2 is working well and file server 1 lose winbind rfc track. # # FILE SERVER 1 - PROBLEM # # tdbdump winbindd_idmap.tdb { key(9) = "USER HWM\00" data(4) = "\D0\07\00\00" } { key(10) = "GROUP HWM\00" data(4) = "\D0\07\00\00" } { key(14) = "IDMAP_VERSION\00"

--On Monday, May 11, 2015 02:26:17 PM -0700 John R Pierce <pierce at hogranch.com> wrote: > never met a unix that didn't come with Perl already installed, or as a > base option SunOS-4 :) Didn't have emacs, either, nor an ANSI-C compiler. And the OS came on QIC-150 tape (ie: 150 MB total capacity). Not that that defeats the argument ... Devin

en fait je vous renvoi ce message car maintenant la taille de la police change au bout de 500 lignes environ, alors que j''avais reussi à garder la taille jusqu''à environ 5000 lignes. Je ne comprend pas. Est-ce que c''est instable? le bout de code que vous m''avez envoyer ne marche pas. merci Sebastien _______________________________________________ wxruby-users

On c7 I can't find mod_perl. Configuring bacula client requires only few lines...with bacula you need only bacula pkgs and one database. With backuppc there are different services to install and configure...some external to centos base. In c7, without mod_perl I must run cgi with suid... Ok bacula is more complex (complexity I mean for its configuration) but It is better organized and less

Dear list members, I am estimating an ordinal generalized estimating equations (GEE) regression model on repeated measurements data. Is there any way (preferably in R) to test the proportional odds assumption of this model? Thanks in advance. Andreas [[alternative HTML version deleted]]

I am using the R statistical package in a pretty straightforward manner, just interested in getting summary statistics and reliable estimates of means, variances, confidence intervals, p-values using standard tests, etc. I've been using the generalized estimating equation package because I often deal with repeatedly sampled pairs of data from the same source, and my reading (and my

I'm sure most people here know about Dash in Debian. Have there been discussions about providing a more efficient shell in Centos for use with heavily invoked non-interactive scripts? With sh being a link to bash in Centos I don't know if it would explode if the link was changed to something else, but at least the scripts we made on our own that run certain services could be changed and

Hi, I'm actually trying to rank a set of candidate models with an information criterion (AICc, QIC, BIC). The problem I have is that I use mixed-effect cox regression only available with the package {coxme} (see the example below). #Model1 >spring.cox <- coxme (Surv(start, stop, Real_rand) ~ strata(Paired)+R4+R3+R2+(R3|Individual), spring) I've already found some explications in

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Dear all, We have got data (response and predictor variables) for each country of the world; I started by fitting standard GLM and tested for spatial correlation using variogram models (geoR) fitted to the residuals of the GLM. Spatial autocorrelation is significant. Therefore, I think about using general estimation equations (geeglm or geese in geepack) allowing for residual spatial

We are currently analyzing data on children clustered in day care-centers (DCC). We have tried to use geepack and gee libraries to estimate an overall incidence rate for absences (=number of absences/risk time) by specifying geese(number.absences ~ offset(log(risktime)), id=day.care.id, family=poisson("log"), data=dcc, corstr="exch",

Good evening, In my research I am studying the marginal models, where the main goal is on the structure of the association. My practical example has cluster with up to 600 observations and with this database, the function geese() return me the following message: This application has requested the runtime to terminate it is on unusual way. Please contact the application’s support team