randomLCA

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randomLCA

Gabriele Accetta
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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Re: randomLCA

Ingmar Visser
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 <
[hidden email]> 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.
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

        [[alternative HTML version deleted]]

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Re: 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 <[hidden email]>:

> 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
> <[hidden email]> 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.
>>
>> ______________________________________________
>> [hidden email] mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>



--
Gabriele Accetta

"E' evidente che non si ha vera democrazia là dove l'accesso
all'istruzione non è garantito in misura pari a tutti i cittadini:
perché, importando necessariamente la diversa cultura una diversa
possibilità di partecipazione alla vita politica, il privilegio
dell'istruzione si risolve necessariamente in privilegio politico."
Piero Calamandrei

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