similar to: Joint confidence intervals for GLS models?

Hi, I'm using RMySQL in order to obtain data from my MySQL server. In my databases sometimes I have columns with names that contain '_' character (ex: 'gdp_capita', 'population_total', etc...). When these names appear as the names of the vectors in the data frame that I get, sometimes I have problems as: > cor(gdp_capita, population_total) Error: object

Hi everyone, I'm using lmer and estimable (from packages lme4 and gmodels respectively) and have the disconcerting happening that when I run exactly the same code, I get different results! In checking this out by running the code 50x, it seems to be that answers may be randomly deviating around those which I get from another stats package (GenStat, using the linear mixed models functionality

Hi, I've data from an incomplete fatorial design. One level of a factor doesn't has the levels of the other. When I use lm(), the summary() return NA for that non estimable parameters. Ok, I understant it. But I use contrast::contrast(), gmodels::estimable(), multcomp::glht() and all these fail when model has NA estimates. This is becouse vcov() and coef() has different dimensions. Is

Hello All, I have posted to this list before regarding the same issue so I apologize for the multiple e-mails. I am still struggling with this issue so I thought I'd give it another try. This time I have included reproducible code and a subset of the data I am analyzing. I am running an ANOVA with three factors: GROUP (5 levels), FEATURE (2 levels), and PATIENT (2 levels), where

> On Sep 7, 2017, at 12:21 PM, Miluji Sb <milujisb at gmail.com> wrote: > > df is a data frame consisting of one variable (iso3 codes) such as > > USA > RUS > ARG > BGD > ITA > FRA > > > Some of these iso3 codes are repeated and I would like the corresponding continent name, the countrycode package does not seem to distinguish between North and

Take the following example: a <- rnorm(100) b <- trunc(3*runif(100)) g <- factor(trunc(4*runif(100)),labels=c('A','B','C','D')) y <- rnorm(100) + a + (b+1) * (unclass(g)+2) m <- lm(y~a+b*g) summary(m) Here b is discrete but not treated as a factor. I am interested in computing the effect of b within groups defined by the

Hello all, I posted a similar question recently but I suspect that it was not well enough formulated to trigger any answers. So I try again: Is there a way to produce boxplots (or something similar) that uses the estimated fixed effects of an lme{nlme} object? When I want to know the mean, I use estimable{gmodels} together with an appropriate matrix. I did look for a similar tool to estimable in

Why do I see this error? > library(stats) > require(stats) [1] TRUE > > tHSD <- TukeyHSD(aov) Error in TukeyHSD(aov) : no applicable method for "TukeyHSD" In case it helps: > aov Call: aov(formula = roi ~ (Cue * Hemisphere) + Error(Subject/(Cue * Hemisphere)), data = roiDataframe) Grand Mean: 8.195069 Stratum 1: Subject Terms: Residuals Sum

df is a data frame consisting of one variable (iso3 codes) such as USA RUS ARG BGD ITA FRA Some of these iso3 codes are repeated and I would like the corresponding continent name, the countrycode package does not seem to distinguish between North and South America. Thanks. Sincerely, Milu On Thu, Sep 7, 2017 at 9:00 PM, David Winsemius <dwinsemius at comcast.net> wrote: > > >

Hi I use gnls to fit non linear models of the form y = alpha * x**beta (alpha and beta being linear functions of a 2nd regressor z i.e. alpha=a1+a2*z and beta=b1+b2*z) with variance function varPower(fitted(.)) which sounds correct for the data set I use. My purpose is to use the fitted models for predictions with other sets of regressors x, z than those used in fitting. I therefore need to

Hello all! R2.0.1, W2k. All packages updated. I?m heavily dependant on using mixed models. Up til?now I have used lme() from nlme as I have been told to. Together with estimable() from gmodels it works smooth. I also often run Rcmdr, mostly for quick graphics. After using Rcmdr, on reopening the R workspace all help libraries for Rcmdr (22 !) loads, among them nlme, but not Rcmdr itself. Why?

Hello all! R2.0.1, W2k I posted this question to the list last Sunday without getting any replies on the list. I got two off the list though, suggesting me to plot "manually" as a second step, from estimable() or intervals() objects respectively. As this was not really what I wished for, I take the risk to upset somebody with a trivial question, and re-post it (just a little

Hi R users, I sent a message yesterday about NA in model estimates ( http://r.789695.n4.nabble.com/How-set-lm-to-don-t-return-NA-in-summary-td3722587.html). If I use aov() instead of lm() I get no NA in model estimates and I use gmodels::estimable() without problems. Ok! Now I'm performing a lot of contrasts and I need correcting for multiplicity. So, I can use multcomp::glht() for this.

Using the "ergoStool" data cited in Mixed-Effects Models in S and S-PLUS by Pinheiro and Bates as an example, we have ======== > library(nlme) > fm <- lme(effort~Type-1, data=ergoStool, random=~1|Subject) > summary(fm) Linear mixed-effects model fit by REML Data: ergoStool AIC BIC logLik 133.1308 141.9252 -60.5654 Random effects: Formula: ~1 | Subject

Dear all, In SAS (GLM and MIXED) estimable functions (linear functions of the parameters) can be specified in the ESTIMATE and CONTRAST statements. Has anyone written a similar "utility" for use in connection with lm? Thanks in advance S?ren H?jsgaard -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

New versions of the Hmisc and Design packages, including ones for Windows, may be found at http://hesweb1.med.virginia.edu/biostat/s/library/r Thanks as always to Xiao Gang Fan <xiao.gang.fan1 at libertysurf.fr> for providing the Windows ports. In Hmisc, new features for multiple imputation have been added to aregImpute and LaTeX and plot methods have been improved for summary.formula

Version 0.6.0 of the gregmisc package has just been released on CRAN. Description: =========== Package: gregmisc Description: Misc Functions written/maintained by Gregory R. Warnes Title: Greg's Miscellaneous Functions Version: 0.6.0 Date: 2002/09/23 Maintainer: Gregory R. Warnes <Gregory_R_Warnes at groton.pfizer.com> Author: Gregory R. Warnes. Includes code provided by Ben

Version 0.6.0 of the gregmisc package has just been released on CRAN. Description: =========== Package: gregmisc Description: Misc Functions written/maintained by Gregory R. Warnes Title: Greg's Miscellaneous Functions Version: 0.6.0 Date: 2002/09/23 Maintainer: Gregory R. Warnes <Gregory_R_Warnes at groton.pfizer.com> Author: Gregory R. Warnes. Includes code provided by Ben

Dear Greg, Thanks for the new release. The decomposition of the SSQ is just what I need! Regards, Martin. Martin Hoyle, School of Life and Environmental Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK Webpage: http://myprofile.cos.com/martinhoyle >>> gregory_r_warnes at groton.pfizer.com 10/30/02 07:16PM >>> Version 0.7.3 of the gregmisc package

Hello, I am using sm.density() to find the bivariate joint PDFof events: For eg, x<-cbind(rnorm(30),rnorm(30)) den<-sm.density(x) Then I get the joint pdf from den$estimate in order to constructthe joint cumulative PDF. However, summing up all the values from den$estimateisnot equal to 1(have multipliedby the grid size). Anyone could help? Thanks. mc [[alternative HTML version