Random effects models of the type fitted by ordinal assume something akin to
compound symmetry, which is not realistic when time between measurements is
long or irregular.
Frank
Rune Haubo-2 wrote
> lmer is not designed for ordered categorical data as yours are. You could
> take a look at the ordi
lmer is not designed for ordered categorical data as yours are. You could
take a look at the ordinal package which is designed for this type of data
including mixed models (function clmm) which you probably want to use.
Best,
Rune
Den 24/03/2011 21.03 skrev "Rasanga Ruwanthi" :
>
> Dear List,
>
>
package msm has some examples with this type of type, ie modeling disease
state transitions in continuous time, using multi-state markov models.
hth, Ingmar
On Thu, Mar 24, 2011 at 6:22 PM, Rasanga Ruwanthi wrote:
> Dear List,
>
> I have some longitudinal data, each patient was followed at times
Dear List,
I have some longitudinal data, each patient was followed at times 0, 12, 16, 24
weeks and measure severity of a illness (0-worse, 1-same, 2-better). So,
longitudinal response is categorical. I was wondering whether lmer in R can
fit a model for this type of data. If so, how we code
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