search for: datkins

...plot(tmp.df$y.tmp ~ tmp.df[,i]) + } ### nothing happens; no error msg; no plotting device opened > xyplot(tmp.df$y.tmp ~ tmp.df[,2]) ### without loop works fine and plots relationship of x1.tmp and y.tmp Can someone see what I'm missing? Any directions/pointers appreciated. cheers, Dave datkins at u.washington.edu

Dear Listers: I used cronbach{psy} to evaluate the internal consistency and some set of variables gave me alpha=-1.1003, while other, alpha=-0.2; alpha=0.89; and so on. I am interested in knowing how to interpret 1. negative value 2. negative value less than -1. I also want to re-mention my previous question about how to evaluate the consistency of a set of variables and about the total

...", rr[,3], "]", sep = ""), x = 1, y = 1:6) errbar(x = factor(row.names(rr)), y = rr[,1], yplus = rr[,3], yminus = rr[,2]) abline(v = 1, lty =2) -- Dave Atkins, PhD Research Associate Professor Department of Psychiatry and Behavioral Science University of Washington datkins at u.washington.edu Center for the Study of Health and Risk Behaviors (CSHRB) 1100 NE 45th Street, Suite 300 Seattle, WA 98105 206-616-3879 http://depts.washington.edu/cshrb/ (Mon-Wed) Center for Healthcare Improvement, for Addictions, Mental Illness, Medically Vulnerable Populations...

...ia a modified version of mcmcsamp(). [Some people are never satisfied, You've written a great piece of software, and users reward you by complaining that they want even more!] John Maindonald. On 1 Jan 2006, at 10:00 PM, r-help-request at stat.math.ethz.ch wrote: > From: Dave Atkins <datkins at u.washington.edu> > Date: 1 January 2006 1:40:45 AM > To: r-help at stat.math.ethz.ch > Subject: Re: [R] lme X lmer results > > > > Message: 18 > Date: Fri, 30 Dec 2005 12:51:59 -0600 > From: Douglas Bates <dmbates at gmail.com> > Subject: Re: [R] lme X lm...

...ut it seems like the intercept coefficients ought to be the same. If the quadratic is dropped, there is no discrepancy between coef() and intevals(), so perhaps this is related to the complexity of the model vs. sparseness of data? Any insights appreciated (data below). Dave -- Dave Atkins, PhD datkins at u.washington.edu tmp.df <- data.frame(id = as.factor(rep(1:8, each=8)), sex = factor(rep(0:1, each=4, length.out=64), 0:1, c("Husband","Wife")), time = rep(0:3, length.out=64),...

...time = rep(1:10, 10), dv = rnbinom(100, mu = 0.5, size = 100)) toy.df library(lattice) xyplot(dv ~ time | id, data = toy.df, type = c("g","l")) -- Dave Atkins, PhD Research Associate Professor Department of Psychiatry and Behavioral Science University of Washington datkins at u.washington.edu Center for the Study of Health and Risk Behaviors (CSHRB) 1100 NE 45th Street, Suite 300 Seattle, WA 98105 206-616-3879 http://depts.washington.edu/cshrb/ (Mon-Wed) Center for Healthcare Improvement, for Addictions, Mental Illness, Medically Vulnerable Populations...

...iglevel), simplify=TRUE) apply(r, 1, mean) } out <- mypower(n = 1000, beta0 = 2.5, beta1 = -0.20, alpha0 = -0.90, alpha1 = 0.20, theta = 2.2, M = 100) out -- Dave Atkins, PhD Research Associate Professor Department of Psychiatry and Behavioral Science University of Washington datkins at u.washington.edu Center for the Study of Health and Risk Behaviors (CSHRB) 1100 NE 45th Street, Suite 300 Seattle, WA 98105 206-616-3879 http://depts.washington.edu/cshrb/ (Mon-Wed) Center for Healthcare Improvement, for Addictions, Mental Illness, Medically Vulnerable Populations...

...02). Clinical significance methods: Which one to use and how useful are they? Behavior Therapy, 33, 529-550. I will send the functions to you back-channel. cheers, Dave -- Dave Atkins, PhD Assistant Professor in Clinical Psychology Travis Research Institute Fuller Theological Seminary Email: datkins at fuller.edu Message: 43 Date: Wed, 11 Feb 2004 10:15:31 +1000 From: "Alistair Campbell" <alistair.campbell at jcu.edu.au> Subject: [R] Clinical significance as a package? To: <r-help at stat.math.ethz.ch> Message-ID: <000d01c3f034$28e27040$691edb89 at alistaircampbel&gt...

Dear r-helpers, I can't get lsa to run because: > library(lsa) Loading required package: Rstem Error in library(pkg, character.only = TRUE, logical = TRUE, lib.loc = lib.loc) : 'Rstem' is not a valid package -- installed < 2.0.0? In addition: Warning message: cannot create HTML package index in: make.packages.html() > install.packages('Rstem') Warning in

...s is where I have run into problems. I experimented with expression() and paste() for a while without luck, and now believe I need to use substitute() (given some of the examples on the plotmath() help-page). But, I can't get the code quite right. Any suggestions appreciated. Dave Atkins datkins at u.washington.edu

Dear All, I'm analysing a negative binomial dataset from a population-based study. Many covariates were determined on household level, so all members of a household have the same value for those covariates. In STATA, there seems to be an option for 'clustered analysis' for neg-bin regression. Does an equivalent exist for R(MASS)'s glm.nb or a comparable function? Many thanks for

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I am writing to inquire about a warning message that I receive when trying to model a random slope and intercept at the second level of a 3-level model. Specifically, I am testing a 3-level model in which time (WEEK) is nested in participants (PARTICIP) and participants are nested in dyads (DYADID). The goal is to examine how an interpersonal style (CORUMTO) one week predicts changes in

Dear R Experts, I am attempting to run a mixed effects model on a within-subjects repeated measures design, but I am unsure if I am doing it properly. I was hoping that someone would be able to offer some guidance. There are 5 independent variables (subject, condition, difficulty, repetition) and 1 dependent measure (value). Condition and difficulty are fixed effects and have 3 levels each

Hi, I am trying to run a multilevel model with time nested in people and people nested in dyads (3 levels of nesting) by initially running a series of models to test whether the slope/intercept should be fixed or random. The problem that I am experiencing appears to arise between the random intercept, fixed slope equation AND. (syntax: rint<-lme(BDIAFTER~BDI+WEEK+CORUMTO,

Hello, Is there a way to compare the relative relevance of fixed and random effects in mixed models? I have in mind measures of effect size in ANOVAs, and would like to obtain similar information with mixed models. Are there information criteria that allow to compare the relevance of each of the effects in a mixed model to the overall fit? Thank you, Bruno

Greetings, 1) Is there a nice way of extracting the variance estimates from an lme fit? They don't seem to be part of the lme object. 2) In a series of simulations, I am finding that with ML fitting one of my random effect variances is sometimes being estimated as essentially zero with massive CI instead of the finite value it should have, whilst using REML I get the expected value. I guess

I'd like to estimate an ordinal logistic regression with a random effect for a grouping variable. I do not find a pre-packaged algorithm for this. I've found methods glmmML (package: glmmML) and lmer (package: lme4) both work fine with dichotomous dependent variables. I'd like a model similar to polr (package: MASS) or lrm (package: Design) that allows random effects. I was

Hi, this is not a new doubt, but is a doubt that I cant find a good response. Look this output: > m.lme <- lme(Yvar~Xvar,random=~1|Plot1/Plot2/Plot3) > anova(m.lme) numDF denDF F-value p-value (Intercept) 1 860 210.2457 <.0001 Xvar 1 2 1.2352 0.3821 > summary(m.lme) Linear mixed-effects model fit by REML Data: NULL AIC BIC

I have a somewhat related question. A while back I was doing some simulations using for() loops, and I wanted to keep track of the iterations using a line of code quite similar to what Dimitris presented below. Instead of printing the iteration message at the end of each iteration (actually, at the end of every 100th), nothing was printed until the for() loop was complete, and *then* all