search for: zeger

Dear all: Y=a+bX1+cX2 In the Gee (Generalized Estimation Equation) arguments: The arument Corstr has sveral choices: "independence" "fixed" "stat_M_dep" "non_stat_M_dep" "exchangeable" "AR-M" "unstructured" What does each term mean? How do I choose among them? How do I know the correlation structure of

...; See also: Swihart, B.J., Caffo, B.S., and Crainiceanu, C.M. (2013). A Unifying Framework for Marginalized Random-Intercept Models of Correlated Binary Outcomes. International Statistical Review, 82 (2), 275-295 1-22. <DOI: 10.1111/insr.12035> Griswold, M.E., Swihart, B.J., Caffo, B.S and Zeger, S.L. (2013). Practical marginalized multilevel models. Stat, 2(1), 129-142. <DOI: 10.1002/sta4.22> Heagerty, P.J. (1999). Marginally specified logistic-normal models for longitudinal binary data. Biometrics, 55(3), 688-698. <DOI: 10.1111/j.0006-341X.1999.00688.x> Heagerty, P.J. and Z...

Hello, Has anyone written R functions for applying self-controlled case series methods (http://statistics.open.ac.uk/sccs/). In fact only thing needed is to modify glm function to allow absorption of effect. Eg. in Poisson model individual effect is used as factor, but it is considered as nuisance term where parameter estimates are not needed. Could anyone point how absorbing individual

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Hi, I'm trying to figure out if there are any packages allowing one to fit mixed models (or non-linear mixed models) to data that includes censoring. I've done some searching already on CRAN and through the mailing list archives, but haven't discovered anything. Since I may well have done a poor job searching I thought I'd ask here prior to giving up. I understand that

I've put all ``current'' add-on packages into CRAN's source/contrib tree and created an INDEX file (attached below). As you can see, currently we have acepack bootstrap ctest date e1071 fracdiff gee jpn snns splines survival4 (Yes, e1071 and jpn are new ... more on the latter in a later mail.) In the near future, I am hoping for the following: oz (Bill

Does anyone know if Hastie's gene shaving method is implemented in R Thanks, Aimin

I have a matrix (1000 x 224) that contains the output from the function boot.array. For each row, there are 224 columns that represent the case numbers of the selected individuals from a bootstrap. The cases are listed in selection order, not numerical order. I'd like to rearrange the cells so that every row has the column entries listed ascending numeric order. I've been able to

I apologise for starting a new thread, but we had a mail problem and I don't have the original message to refer to. Someone mentioned the new "Diamond Graphs" invented at Johns Hopkins. I haven't see the August 2003 issue of The American Statistician yet, but I _have_ read the press release. The press release is a bit of a stunner. I quote: "Who would have thought we

...hich has some functions which appear very promising: http://alpha.luc.ac.be/~lucp0753/rcode.html Thomas Lumley pointed out that instead of NB, one can get a Poisson-Normal mixture out of this by changing the assumption on the error term. He pointed me at some articles that are exactly on point - Zeger (Biometrika 1988, pp621-629) gives an estimation procedure for a time series count model that is based on a Poisson-Normal mixture. - Something more or less similar is discussed by Davis et al (Biometrika 2000, p491-505) And he to consider "sandwich estimators" (or similar) for longitud...

...back: “The exact fitting approach using the GEE model is difficult to understand. The authors should clearly state, that they use a different bias for each individual measurement using the GEE model.” I can’t figure out what the reviewer is talking about. According to my reading of the Liang and Zeger original paper on the Generalized Estimating Equations, there aren’t any biases (as I understand bias) generated in this method. I’m guessing that the reviewer is having trouble with language, and is really referring to the weights assigned to the variances of each of the 15 clusters of data. And...

You may want to take a look at a paper by Julia Kelsall and Scott Zeger in JRSS(C) - 1999, pp. 331-344. This paper describes a frequency domain approach to log-linear regression modeling of poisson-distributed count data, accounting for correlation and over-dispersion. There are also some S functions available to implement the methodology. Ravi. -----Original Message...

hi all- I am doing some research, have never used R before until today and need to understand the following program for a project. if some one could PLEASE help me understand this program ASAP i would GREATLY appreciate it (any syntax/ statistic comments would be great) PLEASE PLEASE HELP!! THANKYOU!!! -on a side note, it seems to me that R doesnt include the pv, and it was calculated

Dear all R users, I have a small doubt about panel data analysis. My basic understanding on Panel data is a type of data that is collected over time and subjects. Vector Autoregressive Model (VAR) model used on this type of data. Therefore can I say that, one of statistical tools used for analysis of panel data is VAR model? If you clarify my doubt I will be very grateful. Thanks and regards,

...e1071 Miscellaneous functions used at the Department of Statistics at TU Wien (E1071). fracdiff Maximum likelihood estimation of the parameters of a fractionally differenced ARIMA(p,d,q) model (Haslett and Raftery, Applied Statistics, 1989). gee An implementation of the Liang/Zeger generalized estimating equation approach to GLMs for dependent data. jpn A function to plot Japan's coast-line and prefecture boundaries. oz Functions for plotting Australias coastline and state boundaries. snns An R interface to the Stuttgart Neural Networks Simulator (S...

...e Department of Statistics at TU Wien (E1071). ffrraaccddiiffff Maximum likelihood estimation of the parameters of a fractionally differenced ARIMA(p,d,q) model (Haslett and Raftery, Applied Statistics, 1989). ggeeee An implementation of the Liang/Zeger generalized estimating equation approach to GLMs for dependent data. jjppnn A function to plot Japan's coast-line and prefecture boundaries. oozz Functions for plotting Australia's coastline and state boundaries. ssnnnnss An R interface to t...

...e Department of Statistics at TU Wien (E1071). ffrraaccddiiffff Maximum likelihood estimation of the parameters of a fractionally differenced ARIMA(p,d,q) model (Haslett and Raftery, Applied Statistics, 1989). ggeeee An implementation of the Liang/Zeger generalized estimating equation approach to GLMs for dependent data. jjppnn A function to plot Japan's coast-line and prefecture boundaries. oozz Functions for plotting Australia's coastline and state boundaries. ssnnnnss An R interface to t...

...used at the Department of Statistics at TU Wien (E1071). fracdiff Maximum likelihood estimation of the parameters of a fractionally differenced ARIMA(p,d,q) model (Haslett and Raftery, Applied Statistics, 1989). gee An implementation of the Liang/Zeger generalized estimating equation approach to GLMs for dependent data. integrate Code for adaptive quadrature. jpn A function to plot Japan's coast-line and prefecture boundaries. leaps A package which performs an exhaustive search for the best...

...used at the Department of Statistics at TU Wien (E1071). fracdiff Maximum likelihood estimation of the parameters of a fractionally differenced ARIMA(p,d,q) model (Haslett and Raftery, Applied Statistics, 1989). gee An implementation of the Liang/Zeger generalized estimating equation approach to GLMs for dependent data. integrate Code for adaptive quadrature. jpn A function to plot Japan's coast-line and prefecture boundaries. leaps A package which performs an exhaustive search for the best...