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MIXNO: a computer program for mixed-effects nominal logistic regression

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  • Hedeker, Donald

Abstract

MIXNO provides maximum marginal likelihood estimates for mixed-effects nominal logistic regression analysis. These models can be used for analysis of correlated nominal response data, for example, data arising from a clustered or longitudinal design. For such data, the mixed-effects model assumes that data within clusters or sub jects are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from nesting of the data. MIXNO uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated along with the (fixed) effects of explanatory variables. Examples illustrating usage and features of MIXNO are provided.

Suggested Citation

  • Hedeker, Donald, 1999. "MIXNO: a computer program for mixed-effects nominal logistic regression," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 4(i05).
    • Handle: RePEc:jss:jstsof:v:004:i05
    DOI: http://hdl.handle.net/10.18637/jss.v004.i05
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    Cited by:

    1. Rhoads Christopher H., 2012. "Problems with Tests of the Missingness Mechanism in Quantitative Policy Studies," Statistics, Politics and Policy, De Gruyter, vol. 3(1), pages 1-25, March.
    2. Meza, Cristian & Jaffrézic, Florence & Foulley, Jean-Louis, 2009. "Estimation in the probit normal model for binary outcomes using the SAEM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1350-1360, February.
    3. Jona Schellekens, 2009. "Family allowances and fertility: Socioeconomic differences," Demography, Springer;Population Association of America (PAA), vol. 46(3), pages 451-468, August.
    4. Steve Johnson & Don J Webber & Wayne Thomas, 2007. "Which SMEs Use External Business Advice? A Multivariate Subregional Study," Environment and Planning A, , vol. 39(8), pages 1981-1997, August.
    5. Anders Skrondal & Sophia Rabe-Hesketh, 2003. "Multilevel logistic regression for polytomous data and rankings," Psychometrika, Springer;The Psychometric Society, vol. 68(2), pages 267-287, June.
    6. Christine E. Grella & Christy K. Scott & Mark A. Foss & Michael L. Dennis, 2008. "Gender Similarities and Differences in the Treatment, Relapse, and Recovery Cycle," Evaluation Review, , vol. 32(1), pages 113-137, February.
    7. Börner, Jan & Shively, Gerald E. & Wunder, Sven & Wyman, Miriam, 2012. "How do rural households respond to economic shocks? Insights from hierarchical analysis using global data," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126143, International Association of Agricultural Economists.

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