Dear mixed-modelers, I'm interested in modelling a dataset using generalized linear mixed models (specifying "family=binomial" with random effects) in which there is temporal autocorrelation in the response. Is there a way to do this in the new lme4 package? I've used the "correlation" argument in the nlme library to specify a correlation structure for least-square means regression, but this option appears not to be implemented in the new lmer call in the lme4 package. Is such a thing possible (and appropriate) at this time? thanks, chris o'brien
lmer and autocorrelation structures
4 messages · Chris O'Brien, Douglas Bates
On 9/6/07, Chris O'Brien <obrienc at email.arizona.edu> wrote:
Dear mixed-modelers,
I'm interested in modelling a dataset using generalized linear mixed models (specifying "family=binomial" with random effects) in which there is temporal autocorrelation in the response. Is there a way to do this in the new lme4 package? I've used the "correlation" argument in the nlme library to specify a correlation structure for least-square means regression, but this option appears not to be implemented in the new lmer call in the lme4 package. Is such a thing possible (and appropriate) at this time? thanks,
Possible, but only in the fortune("Yoda") sense. In other words that
capability is not built into the lme4 package.
I don't think we can comment on the appropriateness of the model
without more information and perhaps a look at the data. However,
until someone writes the code to incorporate an autoregressive
structure into lmer, the question is moot.
On 9/6/07, Douglas Bates <bates at stat.wisc.edu> wrote:
On 9/6/07, Chris O'Brien <obrienc at email.arizona.edu> wrote:
Dear mixed-modelers,
I'm interested in modelling a dataset using generalized linear mixed models (specifying "family=binomial" with random effects) in which there is temporal autocorrelation in the response. Is there a way to do this in the new lme4 package? I've used the "correlation" argument in the nlme library to specify a correlation structure for least-square means regression, but this option appears not to be implemented in the new lmer call in the lme4 package. Is such a thing possible (and appropriate) at this time? thanks,
Possible, but only in the fortune("Yoda") sense. In other words that
capability is not built into the lme4 package.
I don't think we can comment on the appropriateness of the model
without more information and perhaps a look at the data. However,
until someone writes the code to incorporate an autoregressive
structure into lmer, the question is moot.
P.S. If the reference to fortune("Yoda") is too obscure, try
install.packages("fortunes"); library(fortunes); fortune("Yoda")
On 9/6/07, Douglas Bates <bates at stat.wisc.edu> wrote:
On 9/6/07, Douglas Bates <bates at stat.wisc.edu> wrote:
On 9/6/07, Chris O'Brien <obrienc at email.arizona.edu> wrote:
Dear mixed-modelers,
I'm interested in modelling a dataset using generalized linear mixed models (specifying "family=binomial" with random effects) in which there is temporal autocorrelation in the response. Is there a way to do this in the new lme4 package? I've used the "correlation" argument in the nlme library to specify a correlation structure for least-square means regression, but this option appears not to be implemented in the new lmer call in the lme4 package. Is such a thing possible (and appropriate) at this time? thanks,
Possible, but only in the fortune("Yoda") sense. In other words that
capability is not built into the lme4 package.
I don't think we can comment on the appropriateness of the model
without more information and perhaps a look at the data. However,
until someone writes the code to incorporate an autoregressive
structure into lmer, the question is moot.
P.S. If the reference to fortune("Yoda") is too obscure, try
install.packages("fortunes"); library(fortunes); fortune("Yoda")
P.P.S. I have always felt that to qualify as a Yodaism, Simon's first sentence should have been "R this is.", not "This is R."