similar to: Tukey Kramer with ANOVA (glm)

Hello all, Would there be any interest for adding as.data.frame() methods for model objects? Of course there is packages (e.g. broom), but I think providing methods would be more discoverable (and the patch would be small). It is really useful for exporting model results or for plotting. e.g.: as.data.frame.lm <- function(x) { # could get other arguments, e.g. exp = TRUE/FALSE to

Following Duncan Murdoch's off-list comments (thanks again!), here is a more complete/flexible version: as.data.frame.lm <- function(x, ..., level = 0.95, exp = FALSE) { cf <- x |> summary() |> stats::coef() ci <- stats::confint(x, level = level) if (exp) { cf[, "Estimate"] <- exp(cf[, "Estimate"]) ci <- exp(ci) } df <-

>>>>> SOEIRO Thomas via R-devel >>>>> on Fri, 17 Jan 2025 14:19:31 +0000 writes: > Following Duncan Murdoch's off-list comments (thanks again!), here is a more complete/flexible version: > > as.data.frame.lm <- function(x, ..., level = 0.95, exp = FALSE) { > cf <- x |> summary() |> stats::coef() > ci <- stats::confint(x,

Hi! I'm failing to understand the value of the intercept value in a multiple linear regression with categorical values. Taking the "warpbreaks" data set as an example, when I do: > lm(breaks ~ wool, data=warpbreaks) Call: lm(formula = breaks ~ wool, data = warpbreaks) Coefficients: (Intercept) woolB 31.037 -5.778 I'm able to understand that the value of

Hello, R-i-zens. I'm working on an data set with a factorial ANOVA that has a significant interaction. I'm interested in seeing whether the simple effects are different from 0, and I'm pondering how to do this. So, I have my.anova<-lm(response ~ trtA*trtB) The output for which gives me a number of coefficients and whether they are different from 0. However, I want the

Have created sample sinatra cucumber app as suggested on wiki. Tried both env.rb configurations from there and aslaks git repo. With this combination of gems I get the following error doing basic cuc tests When I visit ''/foo'' # features/step_definitions/general.rb:1 PATH_INFO must start with / (Rack::Lint::LintError)

There has recently been some discussion on the list about AD Model builder and the suitability of R for constructing the types of models used in fisheries management. https://stat.ethz.ch/pipermail/r-help/2006-January/086841.html https://stat.ethz.ch/pipermail/r-help/2006-January/086858.html I think that many R users understimate the numerical challenges that some of the typical

hi list, i have to ask you again, having tried and searched for several days... i want to do a TukeyHSD after an Anova, and want to get the adjusted p-values after the Tukey Correction. i found the p.adjust function, but it can only correct for "holm", "hochberg", bonferroni", but not "Tukey". Is it not possbile to get adjusted p-values after

I'm attempting to calculate a regression in R that I normally use Prism for, because the formula isn't pretty by any means. Prism presents the formula (which is in the Prism equation library as Heterologous competition with depletion, if anyone is curious) in these segments: KdCPM = KdnM*SpAct*Vol*1000 R=NS+1 S=(1+10^(X-LogKi))*KdCPM+Hot a=-1*R b=R*S+NS*Hot+BMax c = -1*Hot*(S*MS+BMax) Y

Dear R-users, Half a year ago we put out the R package "glmmADMB" for fitting overdispersed count data. http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html Several people who used this package have requested additional features. We now have a new version ready. The major new feature is that glmmADMB allows Bernoulli responses with logistic and probit links. In addition there

Hi all, Sorry if the subject is a bit irrelevant or hard to understand, I have no idea on what subject should I put down. My company has a samba domain controller. All users must logon before they can gain access to the fileserver and printers. My home also has a samba domain controller. I use it mainly for file sharing on my home network. Now I am planning to purchase a laptop with wireless

Dear List, Some of you have been following the discussion of the GPL and its inclusion in the glmmADMB package we created for R users. I would like to provide a bit of background and include an email we received from Prof. Ripley so that everyone can be aware of how some might use the GPL to try to force access to proprietary software. I think this is interesting because many have voiced the

Hi I am running an lmer which works fine with family=poisson mixed.model<-lmer(nobees~spray+dist+flwabund+flwdiv+round+(1|field),family="poisson",method="ML",na.action=na.omit) But it is overdispersed. I tried using family=quasipoisson but get no P values. This didnt worry me too much as i think my data is closer to negative binomial but i cant find any examples of

Hello, I'm running a simulation study of a multilevel model with binary response using the binomial probit link. It is a random intercept and random slope model. GLMMPQL and lmer fail to converge on a *significant* portion of the *generated* datasets, while MlWin gives reasonable estimates on those datasets. This is unacceptable. Does anyone has similar experiences? Regards, Roel de

Does anyone know how could I get the significant codes from mixed model output fitted with a GEE package? The output I got is the following: GEE: GENERALIZED LINEAR MODELS FOR DEPENDENT DATA gee S-function, version 4.13 modified 98/01/27 (1998) Model: Link: Logit Variance to Mean Relation: Binomial Correlation Structure: Exchangeable Call: gee(formula = bru

Hello, I am using odesolve to simulate a group of people moving through time and transmitting infections to one another. In Matlab, there is a NonNegative option which tells the Matlab solver to keep the vector elements of the ODE solution non-negative at all times. What is the right way to do this in R? Thanks, Jeremy P.S., Below is a simplified version of the code I use to try to do this,

I am using the 'glmmPQL function in the 'MASS' library to fit a mixed effects logistic regression model to simulated data. I am conducting a series of simulations, and with certain simulated datasets, estimation of the random effects logistic regression model unexpectedly terminates. I receive the following error message from R: Error in lme.formula(fixed=zz + arm.long,random=~1 |

I have finally gotten one version of windows 2003 r2 x64 installed as a guest. The bad news is no network. The network tab says it''s a realtek 8139 when I know it is a intel. I tried downloading the intel drivers and they wont install says it''s the wrong hard ware. Is this common that it uses a 8139 as a generic network card? Also the network card shows The

Hello, I am a undergraduate student at DA-IICT,India pursuing Btech in Information and Communication Technology.Major field of my Research is Information Retrieval and Natural Language processing. xapain being an powerful Information retrieval library have attracted me towards implementing stuff learned in class for this project.I have worked on entity search on RDF data,SMS based FAQ

Dear R-users, A recent post (Feb 16) to R-help inquired about fitting a glmm with a negative binomial distribution. Professor Ripley responded that this was a difficult problem with the simpler Poisson model already being a difficult case: https://stat.ethz.ch/pipermail/r-help/2005-February/064708.html Since we are developing software for fitting general nonlinear random effects models we