similar to: summary.table parameter bug (PR#2514)

I sent this in with an old version, but it's in latest version as well. The fix is simple. In the summary.table function, the parameter is calculated incorrectly for a test of independence among all cells when the table is more than 2-way table. Example: Consider X: > X a b c 1 A1 B2 C1 2 A3 BA3 C2 3 A2 B1 C4 4 A1 B2 C3 5 A3 BA3 C2 6 A1 BA3 C1 7 A2 BA3 C2 8 A1

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

Dear netters, Sorry for cross-posting this question. I am sure R-Help is not a research methods discussion list, but we have many statisticians in the list and I would like to hear from them. Any function/package in R would be able to deal with the problem from this researcher? ---------- Forwarded message ---------- From: Heidi Bertels Date: Tue, Jun 5, 2012 at 4:31 PM Subject: How to best

Is there a way to automate fitting and assessing loglinear models for several nominal variables . . . something akin to step or drop1 or add1 for linear or logistic regression? Thanks. --Chris -- Christopher W. Ryan, MD SUNY Upstate Medical University Clinical Campus at Binghamton 40 Arch Street, Johnson City, NY 13790 cryanatbinghamtondotedu "If you want to build a ship, don't drum

Hi all: Here's a question about result of loglinear analysis. There're 2 factors:area and nation.The raw data is in the attachment. I fit the saturated model of loglinear with the command: glm_sat<-glm(fre~area*nation, family=poisson, data=data_Analysis) After that,I extract the coefficients: result_sat<-summary(glm_sat) result_coe<-result_sat$coefficients I find that all the

--- v2v/convert_linux.ml | 18 +++++++++++++++--- 1 file changed, 15 insertions(+), 3 deletions(-) diff --git a/v2v/convert_linux.ml b/v2v/convert_linux.ml index f670812..39a520c 100644 --- a/v2v/convert_linux.ml +++ b/v2v/convert_linux.ml @@ -49,13 +49,14 @@ type kernel_info = { ki_modules : string list; (* The list of module names. *) ki_supports_virtio : bool; (* Kernel has

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

Dear R Users, A would like to fit a loglinear analysis to a three dimensional contingency table. But I Don't want to run a full saturated modell. Is there any package in R that could handle somekind of stepwise search to choose out the best soultion? And how can I fit a non fully saturated modell, which only use the important interactions? Best Regards Zoltan Kmetty [[alternative HTML

--- v2v/convert_linux.ml | 18 +++++++++++++++--- 1 file changed, 15 insertions(+), 3 deletions(-) diff --git a/v2v/convert_linux.ml b/v2v/convert_linux.ml index f670812..420aba5 100644 --- a/v2v/convert_linux.ml +++ b/v2v/convert_linux.ml @@ -49,13 +49,14 @@ type kernel_info = { ki_modules : string list; (* The list of module names. *) ki_supports_virtio : bool; (* Kernel has

On Thursday, 6 April 2017 12:04:21 CEST Richard W.M. Jones wrote: > Previously the kernel_info field 'ki_supports_virtio' really meant > that the kernel supports virtio-net. That was used as a proxy to mean > the kernel supports virtio in general. > > This change splits the field so we explicitly test for both virtio-blk > and virtio-net drivers, and store the results

On Thursday 04 December 2014 10:21:40 Richard W.M. Jones wrote: > --- > v2v/convert_linux.ml | 18 +++++++++++++++--- > 1 file changed, 15 insertions(+), 3 deletions(-) > > diff --git a/v2v/convert_linux.ml b/v2v/convert_linux.ml > index f670812..39a520c 100644 > --- a/v2v/convert_linux.ml > +++ b/v2v/convert_linux.ml > @@ -49,13 +49,14 @@ type kernel_info = { >

Hi, I'm analyzing experimental results where two different events ("T1" and "T2") can occur or not during an experiment. I made my experiments with one factor ("Substrate") with two levels ("Sand" and "Clay"). I would like to know wether or not "Substrate" affects the occurrence probability of the two events. Moreover, for each

Since v2: - Use string_suffix kernel_name "-debug" || string_suffix kernel_name "-dbg" - This requires addition of the string_suffix function and some tests

Hi,Dear all R experts, I am trying to do the 2-way contingency table analysis by fitting the loglinear models. However, I found my table has several empty cells which are theoretically missing values.I have no idea of how to solve them coz we cannot compute the simulated p-value with zero marginals.Does someone have some suggestions? Please help me out, thanks a lot! Cheers, Yan

Dear all, can somebody give me some pointer how I can fit a "linear-by-linear association model" (i.e. loglinear model for the ordinal variables) in R? A brief description can be found here 'https://onlinecourses.science.psu.edu/stat504/node/141'. Thanks for your help

I am looking for help to analyze an unbalanced AB/BA cross-over design by requesting the type III SS ! # Example 3.1 from S. Senn (1993). Cross-over Trials in Clinical Research outcome<-c(310,310,370,410,250,380,330,270,260,300,390,210,350,365,370,310,380,290,260,90,385,400,410,320,340,220) subject<-as.factor(c(1,4,6,7,10,11,14,1,4,6,7,10,11,14,2,3,5,9,12,13,2,3,5,9,12,13))

Hola Comunidad, Tengo una duda, Queria que en un For si fuese ejecutando un proceso desde 1 hasta 5 por poner un ejemplo , y que el resultado se fuese guardando en variables que se llamar Ki, es decir k1, k2, k3... Un ejemplo de como crei que funcionaria y no lo hizo xD for (i in 1:3) { paste("k", i, sep = "") <- sum(1:i) } Esperaba se crearan las variables k1 =

Previously the kernel_info field 'ki_supports_virtio' really meant that the kernel supports virtio-net. That was used as a proxy to mean the kernel supports virtio in general. This change splits the field so we explicitly test for both virtio-blk and virtio-net drivers, and store the results as separate fields. The patch is straightforward, except for the change to the

Hi R-masters! I have a problem and need your help. I have 9 discrete variables with 2 levels each. In exploratory analisys I generate one matrix with chi-square for tables with 2 ariables each with this script setwd("F:/") dados<-read.csv("log.csv")[,2:10] dados.x<-matrix(NA,ncol=9,nrow=9) for(i in 1:8){ for(j in (i+1):9){ tab<-table(dados[,i],dados[,j])

Hi there! I'm not sure I can create a minimal example of my problem, so I'm linking to a minimal .RData file that has only two objects: obs and exp, each is a 6x9 matrix. http://dl.dropbox.com/u/10364753/test.RData link to dropbox file (I hope this is acceptable mailing list etiquette!) Here's what happens: > obs[1, 1] [1] 118 > exp[1, 1] [1] 118 > obs[1, 1]-exp[1, 1] [1]