similar to: hi: I am newbie for R too...

I am fairly new to log-linear modelling, so as opposed to trying to fit modells, I am still trying to figure out how it actually works - hence I am looking at the interpretation of parameters. Now it seems most people skip this part and go directly to measuring model fit, so I am finding very few references to actual parameters, and am of course clear on the fact that their choice is irelevant for

Dear R-helpers, Im trying to fit a Log-linear model on a dataset with bird counts from 60 sites over 14 years for 12 months each (factors for the models). One of the aims is to predict the missing values in this dataset with model predictions. Ive first tried to work with GLM's, that worked fine except for models with one or more interaction-terms. The GLMs run, run .. for hours. So I

Hello, I'm planning to start using R. Before getting into it, I'd like to ask a couple of questions. Does R carry out loglinear model analysis? That is, will it provide the chi-squared goodness of fit test statistic for a given hierarchical loglinear model? Maybe even do a model selection procedure (like Brown's two-step procedure, or forward/backward selection)? Thanks

I have been tinkering with mosaicplot() and friends as a way of learning R. As part of this, I've written a pair.table() method for mosaic matrices, and would like to extend mosaicplot to work with loglin and logln (MASS) objects. I'm using R 1.4.0 on Win 98. I've been trying to figure out the formula interface, and think there's a bug, but not sure how to find it, yet alone fix

Hello All: I know the function loglin() and loglm() from librarary(MASS) performs analysis on nominal categorical data. Are there any libraries, functions or examples available for analysis of ordinal categorical data? I have in mind procedures that can replicate results in Alan Agresti (1984) "Analysis of Ordinal Categorical Data." Thanks, ANDREW

Hi, We have some sample data from the US census, and we know the marginal totals for the population. We need to make the population estimates add up to the correct sums. I have two questions: Is there some package in R which does this adjustment, by any means? Is there some more modern reference for this problem than Deming's 1943 monograph, ``Statistical Adjustment of Data''?

Hello to all, I recently downloaded R to my PC and am enjoying getting acquainted with it. Thank you to everyone involved in the R-project! I am interested in doing a log-linear analysis with R on a data set with dichotomous variables. There are 11 variables (columns) and around 1000 subjects (rows). How do I aggregate my data, i.e. how do I make a new dataset that includes the variable giving

Hi, It appears that there is no package for estimating log linear models (L. Goodman's family) for data in the form of frequency tables. Am I wrong? Thanks Marwan Khawaja Research Coordinator Fafo, Institute for Applied Social Science N-0608 Oslo, Norway Tel +47 22 08 86 00 +47 22 08 86 94 (Direct) +47 22 67 33 05 (Private) Fax +47 22 08 87 00

Hello, I am almost new in R, so perhaps my question will be silly. I try to use R for analyzing capture-recapture data in epidemiology. A cancer registry has different sources of patients. We know in each list, patients already known in all other list. The aim is to use capture-recapture models for estimating the number of patients unknow of all the sources. Because no order in sources, one

Hello, at the moment I am doing quite a lot of regression, especially logistic regression, on 20000 or more records with 30 or more factors, using the "step" function to search for the model with the smallest AIC. This takes a lot of time on this 1.8 GHZ Pentium box. Memory does not seem to be such a big problem; not much swapping is going on and CPU usage is at or close to

Estimados, Existe algún package especifico para modelos lob lineales en R? Idealmente algo que funcione como el programa LEM. Muchas gracias por su ayuda, Saludos -- Pablo Reyes [[alternative HTML version deleted]]

Hello everybody, Can anyone tell me how I could analyze data that are at a contigency table form? I already found function cfa in the cfa package but I still don't understand how I could use this function in order to elaborate a contigency table. Every answer is welcome! --------------------------------- ÁðïêôÞóôå ôçí äùñåÜí óáò@yahoo.gr [[alternative HTML version deleted]]

Dear R users, I have a large individual-level dataset (~700,000 records) which I am performing a conditional logistic regression on. Key variables include the dichotomous outcome, dichotomous exposure, and the stratum to which each person belongs. Using this individual-level dataset I can successfully use clogit to create the model I want. However reading this large .csv file into R and running

Dear R-help community, I am working with multidimensional contingency tables and I am having trouble getting loglm to run on all dimensions without typing out each dimension. I have generated random data and provided output for the results I want below: d1.c1 <- rnorm(20, .10, .02) d1.c2 <- rnorm(20, .10, .02) d2.c1 <- rnorm(20, .09, .02) d2.c2 <- rnorm(20, .09, .02) d3.c1 <-

Bug report: there is a problem with loglm (or some underlying code) when used with updating within a function. For example, this code works as expected, when used outside a function: ------------------------------------------------- library(MASS)

Hello All R Users, Function loglm() in library MASS can be cajoled to accomodate structural zeros in a cross-classification table. An example from Fienberg demonstrates how this can be done. My question is: Can the function glm() perform the same task? Can glm() estimate a log-linear model with fixed zeros like loglm()? Thanks for your help, Andrew ## Fienberg, The Analysis of Cross-Classified

Dear R users, Is it possible to use a generalized linear model to do a binomial comparison of one list of proportions with a matched list of proportions to test for a difference? So, for example: list 1 list 2 a1 | b1 a2 | b2 3 | 4 7 | 9 6 | 7 5 | 1 9 | 1 3 | 1 I want to compare list 1 with list 2 and the samples

Hi all, I've been running loglinear models for three-way tables: one of the variables having three levels, and the other two having two levels each. An example looks like below: > yes.no <- c("Yes","No") > switch <- c("On","Off") > att <- c("BB","AA","CC") > L <- gl(2,1,12,yes.no) > T <-

I received the following email note re: the vcdExtra package > A vcd update has shown that packages TIMP and vcdExtra are not > declaring their dependence on colorspace/MASS: see > > http://cran.r-project.org/web/checks/check_results_vcdExtra.html But, I can't see what to do to avoid this, nor understand what has changed in R devel. Sure enough, CRAN now reports errors in

Dear all, sorry to bother you all with this but I've been trying to use the loglm in MASS package (v2.8.0) and cannot get any sensible output. I'm wondering am I doing something very foolish or missing something obvious. For example, I tried the documentation help(loglm) example - here's the code # Case 1: frequencies specified as an array. sapply(minn38,