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help for geekel2d                                          Jean-Benoit Hardouin
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Estimation of the parameters of undimensional and bidimensional IRT models

        geekel2d varlist [, coef(matrixname) nbit(#) critconv(#) ll
              quad(#) novar]

        varlist is a list of two existing dichotomous variables or
              more.

Description

    geekel2d estimates, by Generalized Estimating Equations (GEE), the
        parameters of the model defined by Kelderman (1994) with one or two
        dimensions and dichotomic items. This model includes the Rasch model
        and the One Parameter Logistic Model (OPLM) for the unidimensional
        models, the Multidimensional Generalized Rasch Model (MGRM) and the
        Multidimensional Completely Sufficient Rasch Model (MMSRM) for the
        two-dimensional models.

Options

    coef is the name of a matrix which contains the coeficients B. This
        matrix relies the items and the latent traits. Each row represents an
        item and there is as many colmuns than the supposed number of latent
        traits (one or two).  The coefficients are choosen, in general, among
        the first intergers, but geekel2d allows using real coefficients. By
        default, the Rasch model is supposed (the matrix coef is a vector of
        1).

    nbit defines the maximal number of iterations in the estimation
        algorithm. By default, this number is fixed to 30.

    critconv is the value of the convergence criterion, calculated as the
        square of the cross-product of the vector containing the difference
        between two successive iterations of the parameters estimations. By
        default, this criterion is fixed to 1e-15.

    ll estimates the marginal log-likelihood and the Akaike Information
        Criterion (AIC) by Gauss-Hermite quadratures.

    quad defines the number of nodes of quadratures.

    novar avoids to compute the standards errors of the estimators (faster).

Remarks

    For detailed informations on the Kelderman model, see Kelderman and
        Rijkes (1994) or Adams and al. (1997).

    geekel2d don't allows using of polytomous items.

    The ghquadm Stata module is needed (use findit ghquadm to obtain it).


Example

    . geekel2d item1 item2 item3 item4 /*Rasch model*/

    . matrix B=(1,0\1,0\0,1\0,1)

    . geekel2d item1 item2 item3 item4 , coef(B) nbit(50) critconv(1e-30)


References

    Kelderman H. and Rijkes C. P. M., Loglinear multidimensional IRT models
        for polytomously scored items. Psychometrika, 1994, 59, 149-176.

    Adams R. J., Wilson M. R. and Wang W., The multidimensional random
        coefficient multinomial logit model. Applied Psychological
        Measurement, 1997, 21, 1-23.

Author

    Jean-Benoit Hardouin, Regional Health Observatory (ORS) - 1, rue Porte
        Madeleine - BP 2439 - 45032 Orleans Cedex 1 - France. You can contact
        the author at jean-benoit.hardouin@orscentre.org and visit the