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From Stata to aML

Author

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  • Sara Ayllon

    (Universitat de Girona)

Abstract

In this article, I explain how to exploit Stata to run multilevel multiprocess regressions with applied maximum likelihood (aML). I show how a single do-file can prepare the dataset, write the control files, input the starting values, and run the regressions without the need to manually open the aML’s Command Prompt window. If desired, results can be brought back to Stata for postestimation. I also provide an example that illustrates how well Stata and aML work together. Copyright 2014 by StataCorp LP.

Suggested Citation

  • Sara Ayllon, 2014. "From Stata to aML," Stata Journal, StataCorp LP, vol. 14(2), pages 342-362, June.
    • Handle: RePEc:tsj:stataj:v:14:y:2014:i:2:p:342-362
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    Cited by:

    1. Sara Ayllón, 2015. "Youth Poverty, Employment, and Leaving the Parental Home in Europe," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 61(4), pages 651-676, December.
    2. Ayllón, Sara & Fusco, Alessio, 2017. "Are income poverty and perceptions of financial difficulties dynamically interrelated?," Journal of Economic Psychology, Elsevier, vol. 61(C), pages 103-114.
    3. Sara Ayllón & András Gábos, 2017. "The Interrelationships between the Europe 2020 Poverty and Social Exclusion Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(3), pages 1025-1049, February.

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