1971Journal of the American Statistical AssociationRequires access

The Asymptotic Distribution of Conditional Likelihood Ratio Tests

Erling B. Andersen

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Abstract

A conditional likelihood ratio test for testing a hypothesis concerning structural parameters in the presence of infinitely many incidental parameters is suggested. It is shown that the usual X2 approximation to the log-likelihood ratio fails to work in many situations involving incidental parameters. In contrast it is shown that the X2 approximation can be used in large samples under fairly general assumptions if we use conditional likelihood ratio tests instead. The relationship between the theory of UMPU-test and conditional likelihood ratio tests is discussed, and some examples are given to show that the conditional likelihood ratio approach covers more cases than the UMPU approach.

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A conditional likelihood ratio test for testing a hypothesis concerning structural parameters in the presence of infinitely many incidental parameters is suggested. It is shown that the usual X2 approximation to the log-likelihood ratio fails to work in many situations involving incidental parameters. In contrast it is shown that the X2 approximation can be used in large samples under fairly general assumptions if we use conditional likelihood ratio tests instead. The relationship between the theory of UMPU-test and conditional likelihood ratio tests is discussed, and some examples are given to show that the conditional likelihood ratio approach covers more cases than the UMPU approach.

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Available abstract

A conditional likelihood ratio test for testing a hypothesis concerning structural parameters in the presence of infinitely many incidental parameters is suggested. It is shown that the usual X2 approximation to the log-likelihood ratio fails to work in many situations involving incidental parameters. In contrast it is shown that the X2 approximation can be used in large samples under fairly general assumptions if we use conditional likelihood ratio tests instead. The relationship between the theory of UMPU-test and conditional likelihood ratio tests is discussed, and some examples are given to show that the conditional likelihood ratio approach covers more cases than the UMPU approach.

Key concepts: Likelihood-ratio test, Likelihood principle, Mathematics, Score test, Marginal likelihood, Conditional probability distribution, Restricted maximum likelihood, Statistics

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