lgrgtest: Lagrange-multiplier test after constrained maximum-likelihood estimation

Tauchmann H (2023)


Publication Type: Journal article, Original article

Publication year: 2023

Journal

Book Volume: 23

Pages Range: 386–401

Journal Issue: 2

DOI: 10.1177/1536867X231175265

Abstract

Besides the Wald and likelihood-ratio tests, the Lagrange multiplier test (Rao, 1948, Mathematical Proceedings of the Cambridge Philosophical Society 44: 50–57; Aitchison and Silvey, 1958, Annals of Mathematical Statistics 29: 813–828; Silvey, 1959, Annals of Mathematical Statistics 30: 389–407) is the third canonical approach to testing hypotheses after maximum likelihood estimation. While the Stata commands test and lrtest implement the first two, Stata does not have an official command for implementing the third. The community contributed boottest package (Roodman et al., 2019, Stata Journal 19: 4–60) focuses on methods of bootstrap inference and also implements the Lagrange multiplier test functionality. In this article, I introduce the new community contributed postestimation command lgrgtest, which allows for straightforwardly using the Lagrange multiplier test after constrained maximum-likelihood estimation. lgrgtest is intended to be compatible with all Stata estimation commands that use maximum likelihood and allow for the options constraints(), iterate(), and from(). lgrgtest can also be used after cnsreg.

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How to cite

APA:

Tauchmann, H. (2023). lgrgtest: Lagrange-multiplier test after constrained maximum-likelihood estimation. Stata Journal, 23(2), 386–401. https://dx.doi.org/10.1177/1536867X231175265

MLA:

Tauchmann, Harald. "lgrgtest: Lagrange-multiplier test after constrained maximum-likelihood estimation." Stata Journal 23.2 (2023): 386–401.

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