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Hello everybody :-) I have some data that I want to model with a logistic regression, most of the independent variables are numeric and the only dependent is categorical, I was thinking that I could apply a logistic regression using glm but I wanted to deepen my knowledge of this so I tried to do some reading and found the "iris" dataset, now I would like to ask two things, first

Suppose that we have o 2-D contingency table where the row variable is nominal and the column one is ordinal. In SAS it is possible to compute the statistic named as row mean scores differ. How can we programmed it in R? (See also Aggresti (2002), Categorical Data Analysis, p. 302) With regards --------------------------------- [[alternative HTML version deleted]]

Dear R-list, Hi everyone, Im trying to make an analysis of multidimensional contingency tables using R. I' working with the Agresti example where you have the data from 3 categories. The thing is how can I do the analisys using the G2 statistics. Somebody can send me an Idea? I attach the program where you can find the data. Best Regards, > prob1<-

Hi, Can one tell me which procedure will fit an ordinal logistic regression model for longitudinal data set. To be precise, I have both dichotomous and polytomous items. Also, I would like to specify different covariance structures (unstructured, ar1 etc) for trial runs. Thanks -- View this message in context:

dear colleagues, I want to use hierarchical partitioning methods to evaluate variance contributions of differente predictors within a generalized linear mixed model framework. I don't know if this is possible, because I can not found anything about this issue. My error is poisson and I, at least, a random factor in the designed analysis. I acknowledge any idea about how deal with

Hello, Is there anywhere I can find some Bayesian Code for 2 by 2 tables or even the non-central hypergeometric distribution in R? Packages would be helpful but the actual coding in R is much better. Thanks, Thanks Jim [[alternative HTML version deleted]]

Hello, I am searching for an R-Package that does an exentsion of the Mantel-Haenszel test for ordinal data as described in Liu and Agresti (1996) "A Mantel-Haenszel type inference for cummulative odds ratios". in Biometrics. I see packages such as Epi that perform it for binary data and derives a varaince for it using the Robbins and Breslow variance method. As well as another pacakge

Dear friends, My R*C table is as follow: better good bad Goup1 16 71 37 Group2 0 4 61 Group3 1 6 57 Can I test if there are statistical significant between Group1 and Group2, Group2 and Group3, Group1 and Group2, taking into the multiple comparisons? The table can be set up using the following program: a<-matrix(data=c(16,71,37,0,4,61,1,6,57),nrow=3,byrow=TRUE) Thanks

Dear R help gurus, I have the following problem and I would be delighted if you could help me. >From a large (1500) cohort of patients we have been taking some measurements (ECG measurements, but its not important). The measurements are ordinal in 4 grades (Grade I-IV, grade IV being the most severe form). Every patients has been measured several times (usually once per year). The

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Hi everyone, I am trying to construct a glm and am running into a couple of questions. The data set I am using consists of 6 categories for the response and 6 independent predictors representing nutrient concentrations at sample point locations. Ultimately I'd like to use the probabilities for each response category in a simulation model such that these probabilities are used to define a

I'd like to estimate an ordinal logistic regression with a random effect for a grouping variable. I do not find a pre-packaged algorithm for this. I've found methods glmmML (package: glmmML) and lmer (package: lme4) both work fine with dichotomous dependent variables. I'd like a model similar to polr (package: MASS) or lrm (package: Design) that allows random effects. I was