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merlin—A unified modeling framework for data analysis and methods development in Stata

Author

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  • Michael J. Crowther

    (University of Leicester
    Karolinska Intitutet)

Abstract

The challenges in statistics and data science are rapidly growing be- cause access to a multitude of data types continues to increase, as well as the sheer quantity of data. Analysts are now presented with multivariate data, sometimes measured repeatedly, and often requiring the ability to model nonlinear relation- ships and hierarchical structures. In this article, I present the merlin command, which attempts to provide an extremely general framework for data analysis. From simple settings such as fitting a linear regression model or a Weibull survival model to more complex settings such as fitting a three-level logistic mixed-effects model or a multivariate joint model of multiple longitudinal outcomes (of different types) and a recurrent event and survival with nonlinear effects, merlin can fit them all. I will take a single dataset and attempt to show you the full range of capabilities of merlin and discuss some future directions for the implementation in Stata.

Suggested Citation

  • Michael J. Crowther, 2020. "merlin—A unified modeling framework for data analysis and methods development in Stata," Stata Journal, StataCorp LP, vol. 20(4), pages 763-784, December.
    • Handle: RePEc:tsj:stataj:y:18:y:2018:i:4:p:763-784
    DOI: 10.1177/1536867X20976311
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    Cited by:

    1. Medina-Olivares, Victor & Lindgren, Finn & Calabrese, Raffaella & Crook, Jonathan, 2023. "Joint models of multivariate longitudinal outcomes and discrete survival data with INLA: An application to credit repayment behaviour," European Journal of Operational Research, Elsevier, vol. 310(2), pages 860-873.

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