Journal ArticleDOI
The Likelihood Ratio, Wald, and Lagrange Multiplier Tests: An Expository Note
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TLDR
In this paper, it was shown that if the log-likelihood function is quadratic then the three test statistics are numerically identical and have χ2 distributions for all sample sizes under the null hypothesis.Abstract:
By means of simple diagrams this note gives an intuitive account of the likelihood ratio, the Lagrange multiplier, and Wald test procedures. It is also demonstrated that if the log-likelihood function is quadratic then the three test statistics are numerically identical and have χ2 distributions for all sample sizes under the null hypothesis.read more
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Structural equation modeling in practice: a review and recommended two-step approach
TL;DR: In this paper, the authors provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development, and present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests.
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Structural Equations with Latent Variables.
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Elements of large-sample theory
TL;DR: The most useful parts of large-sample theory are accessible to scientists outside statistics and certainly to master's-level statistics students who ignore most of measure theory as discussed by the authors, which constitutes a coherent body of concepts and results that are central to both theoretical and applied statistics.
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The Event Study Methodology Since 1969
TL;DR: In this article, the authors discuss the event study methodology, including hypothesis testing, the use of different benchmarks for the normal rate of return, the power of the methodology in different applications and the modeling of abnormal returns as coefficients in a (multivariate) regression framework.
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Applied Multivariate Analysis
TL;DR: In this article, the Multivariate Normal Distribution, Multivariate Normality, and Covariance Structure were used for one-and two-sample tests to compare the performance of vector and matrix algebra.
References
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Journal ArticleDOI
The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics
Trevor Breusch,Adrian Pagan +1 more
TL;DR: The Lagrange multiplier (LM) statistic as mentioned in this paper is based on the maximum likelihood ratio (LR) procedure and is used to test the effect on the first order conditions for a maximum of the likelihood of imposing the hypothesis.
Journal ArticleDOI
Elements of Econometrics.
Ian Domowitz,Jan Kmenta +1 more
TL;DR: The Elements of Econometrics as mentioned in this paper is a textbook for upper-level undergraduate and master's degree courses and may usefully serve as a supplement for traditional Ph.D. courses in economics.
Journal ArticleDOI
A Simple Test for Heteroscedasticity and Random Coefficient Variation.
Trevor Breusch,Adrian Pagan +1 more
TL;DR: In this paper, a simple test for heteroscedastic disturbances in a linear regression model is developed using the framework of the Lagrangian multiplier test, and the criterion is given as a readily computed function of the OLS residuals.
Book
Elements of econometrics
TL;DR: The emphasis is on simplification whenever possible, assuming the readers know college algebra and basic calculus, and Jan Kmenta explains all methods within the simplest framework, and generalizations are presented as logical extensions of simple cases.