similar to: question on lmer function

.. I am new to R but experienced in SAS. SAS has the capability to let me develop a model from a sample and use the results to score the records of another file which won't fit in memory. Is this straightforward in R or does it require coding to do the scoring in segments? Can someone point me to sample code that I can copy or modify to do this quickly? -- Richard Palmer Home 508

I am having trouble generating a graph. I want to know the % of respondents who answered that they "strongly agree" or "agree" the "America owes R's ethnic group a better chance" (BTTRCHNC) and I want to organize it by racial group (RACESHRT). "BTTRCHNC" is organized ordinally from 1 through 5 with 1=Strongly Agree, 5=Strongly Disagree

I came across the package 'ineq' that computes a variety of inequality measures (e.g. gini, theil etc). I want to compute the Theil index (racial segregation) and decompose the total into sub-components (by geog levels). I think the package doesn't report the decomposition (correct me if I'm wrong). Just wonder is that available elsewhere? K.

Sorry for starting another topic, this is actually a reply to Segher's post on Sun Oct 22 on the 'mdct question' topic. I wasn't subscribed properly and so I didn't get email confirmation and thus can't add to that thread. So Segher, if the equation is indeed what you say it is, then replacing mdct_backward with this version should work, but it doesn't. Am I applying

Hi, Can someone tell me which MDCT and invMDCT equation uses? I implemented the invMDCT one given in eusipco.corrected.ps file (handed out by Monty way back) and it produces different time domain samples. I tried both the FFT method and the slow way directly from the equation and couldn't reproduce the results from the original code. This leads me to believe that the forward MDCT used in

I am using the package nlme to fit a simple random effects (variance components model) with 3 parameters: overall mean (fixed effect), between subject variance (random) and within subject variance (random). I have 16 subjects with 1-4 obs per subject. I need a 3x3 variance-covariance matrix that includes all 3 parameters in order to compute the variance of a specific linear

I am wanting to plot a 95% confidence band using segplot, yet I am wanting to have groups. For example if I have males and females, and then I have them in different races, I want the racial groups in different panels. I have this minor code, completely made up but gets at what I am wanting, 4 random samples and 4 samples of confidence, I know how to get A & B into one panel and C&D in to

Dear list, I am currently writing up some of my R models in a more formal sense for a paper, and I am having trouble with the notation. Although this isn't really an 'R' question, it should help me to understand a bit better what I am actually doing when fitting my models! Using the analysis of co-variance example from MASS (fourth edition, p 142), what is the correct notation for the

I am trying to fit a linear mixed model of the form y_ij = X_ij \beta + delta_i + e_ij where e_ij ~N(0,s^2_ij) with s_ij known and delta_i~N(0,tau^2) I looked at the ecme routine in package:pan, but this routine does not allow for different Vi (variance covariance matrix of the e_i vector) matrices for each cluster. Is there an easy way to fit this model in R or should I bite the bullet and

WinXP, R-2.9.1 LS., I have been trying to solve a (for me) tricky issue. No matter what I've tried, I just can't find a way to do this. This is the issue: I have a text file (ansi text) "titles.txt" with lines of text; here is an example of such a file: >>>>> a brief history of polio vaccines anti-vaccination movements and their interpretations early warning

Hello R users! I've been experimenting with lmer to estimate a mixed model with a dichotomous dependent variable. The goal is to fit a hierarchical model in which we compare the effect of individual and city-level variables. I've run up against a conceptual problem that I expect one of you can clear up for me. The question is about random effects in the context of a model fit with a

Now that I have winbind working, life is good. However, I've hit upon a real kick in the pants. As you can see from my email address, we have a convention here of usernames being firstname.lastname. So, when I go to change the owner ship of a file: $ chown chris.palmer myfile Linux thinks I mean user chris, group palmer, and says "invalid group" (there is no palmer group,

I should'nt have sent the last mail so fast. Same problem with \eqn{u_j = a_j + b x + c x^2, \quad j=1, \ldots, r-1} {u[j] = a[j] + b*x + c*x^2 j = 1,\dots,r-1} I thought the problem in the first case could have to do with the use use of \mbox{} (with the braces) within the arguments of \eqn, but here there are none braces in the arguments of \eqn{}{}. Another case giving the

Dear useRs (called Frank Harrell, most likely), after having preached for years to my medical colleagues to be cautious with stepwise selection procedures, they chanted back asking for an alternative when using mixed models. There is a half dozen laXXX packages around for all types of linear models, but as far I see there is none for mixed models such as lme. Even boot.stepAIC (which I

Hi all, This could be naivety/stupidity on my part rather than a problem with model output, but here goes.... I have fitted a fairly simple model m1<-glm(count~siteall+yrs+yrs:district,family=quasipoisson,weights=weight,data=m[x[[i]],]) I want to know if yrs (a continuous variable) has a significant unique effect in the model, so I fit a simplified model with the main effect ommitted...

Dear R users, I use R 2.4.0 on an iMac running Mac OS X 10.4.8, with a 2.16GHz Intel Core 2 Duo and 2GB 667 MHz DDR2 SDRAM. > sessionInfo() R version 2.4.0 (2006-10-03) i386-apple-darwin8.8.1 locale: es_ES.UTF-8/es_ES.UTF-8/es_ES.UTF-8/C/es_ES.UTF-8/es_ES.UTF-8 attached base packages: [1] "methods" "stats" "graphics" "grDevices"

Buenas tardes chicos, estoy intentando hacer un gráfico que resuma para cada dia de la semana la información de algunos distritos específicos de los que contiene mi variable, ejecuto esta sintaxis pero me da un error Error: Mapping should be created with `aes() or `aes_()`. Alguien me puede orientar sobre que estoy haciendo mal, llevo mucho rato atascada. Muchas gracias df_nuevofinal %>%

Hi, I am using lmer (from the package lme4) to predict a binary response variable (REL) from a bunch of fixed effects and two random effects (Speaker_ID and NPhead_lemma): fit <- lmer(REL ~ SPEAKER_GENDER + log(SPEECHRATE) + SQSPEECHRATE + ..... + (1|Speaker_ID) + (1|NPhead_lemma), family="binomial", data=data.lmer, method="Laplace", model=T, x=T) I

See screenshot. :) Is this supposed to work, or should I use a different, non- at google.com account? Thanks for any clues. -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.llvm.org/pipermail/llvm-dev/attachments/20191115/e8f5e795/attachment-0001.html> -------------- next part -------------- A non-text attachment was scrubbed... Name:

https://bugs.freedesktop.org/show_bug.cgi?id=71659 Priority: medium Bug ID: 71659 Assignee: nouveau at lists.freedesktop.org Summary: [NVD9] Hangs under load with ![ PFIFO][0000:01:00.0] unhandled status 0x00800000 QA Contact: xorg-team at lists.x.org Severity: normal Classification: Unclassified