[R] randomLCA

[Gabriele Accetta]

Dear Ingmar, thank you for your email.

This means that a non-random latent class model for a 2x2x2 table (3
diagnostic tests) and 2 latent classes produces a saturated model. The
predicted frequencies equal the observed frequencies.

Is there any reason to introduce  random effects in a saturated model?

thanks
gabriele

2012/8/28 Ingmar Visser <i.visser at uva.nl>:
> use str(dentistry.lca2) to see all values of the output; among them a value
> np for number of parameters, in this case 5*2 for the 5 binary items of 2
> classes + 1 for the class proportions, total 11.
> hth, Ingmar
>
> On Mon, Aug 27, 2012 at 6:05 PM, Gabriele Accetta
> <gabriele.accetta at gmail.com> wrote:
>>
>> Can anybody, please, explain me how many parameter are estimated using
>> randomLCA?
>>
>> For examples,  model  "dentistry.lca2random"   estimate 1 scale (or
>> variance, b_j)  parameter  and 2 position parameters (a_cj)? Doesn't
>> it?
>> Do I need at least 4 diagnostic tests for such a model?
>>
>> What happens if I specify options blocksize and byclass? How many
>> diagnostic tests (or rater) I need?
>>
>>
>> Extract from see "randomLCA examples", by Ken Beath.
>>
>> > dentistry.lca2random <- randomLCA(dentistry[,
>> + 1:5], freq = dentistry$freq, initmodel = dentistry.lca2,
>> + nclass = 2, random = TRUE, quadpoints = 31,
>> + probit = TRUE)
>>
>>
>> Thank you.
>>
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>
>



-- 
Gabriele Accetta

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