LIKELIHOOD RATIO TEST FOR MEAN VECTOR WITH SPECIFIED DIRECTION BASED ON CONDITIONAL DISTRIBUTION

Journal of the Japanese Society of Computational Statistics ◽

10.5183/jjscs1988.15.53 ◽

2002 ◽

Vol 15 (1) ◽

pp. 53-64

Author(s):

Tsunehisa Imada ◽

Hideyuki Douke

Keyword(s):

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Conditional Distribution ◽

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Power of the likelihood ratio test on the mean vector of the multivariate normal distribution with missing observations

10.1093/biomet/60.2.365 ◽

1973 ◽

Vol 60 (2) ◽

pp. 365-368 ◽

Author(s):

DONALD F. MORRISON ◽

DINESH S. BHOJ

Keyword(s):

Normal Distribution ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Multivariate Normal Distribution ◽

Missing Observations ◽

Multivariate Normal ◽

The Mean ◽

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A modified likelihood ratio test for a mean vector with monotone missing data

Discussiones Mathematicae Probability and Statistics ◽

10.7151/dmps.1194 ◽

2017 ◽

Vol 37 (1-2) ◽

pp. 39

Author(s):

Takashi Seo ◽

Muni S. Srivastava ◽

Ayaka Yagi

Keyword(s):

Missing Data ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Modified Likelihood Ratio Test ◽

Modified Likelihood ◽

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An approximate likelihood ratio test for a normal mean vector with nonnegative components with application to clinical trials

10.1093/biomet/76.3.577 ◽

1989 ◽

Vol 76 (3) ◽

pp. 577-583 ◽

Author(s):

DEI-IN TANG ◽

CLARE GNECCO ◽

NANCY L. GELLER

Keyword(s):

Clinical Trials ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Approximate Likelihood Ratio Test ◽

Normal Mean ◽

Approximate Likelihood ◽

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Accurate Critical Constants for the One-Sided Approximate Likelihood Ratio Test of a Normal Mean Vector When the Covariance Matrix Is Estimated

10.1111/j.0006-341x.2002.00650.x ◽

2002 ◽

Vol 58 (3) ◽

pp. 650-656 ◽

Author(s):

Ajit C. Tamhane ◽

Brent R. Logan

Keyword(s):

Covariance Matrix ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Approximate Likelihood Ratio Test ◽

Normal Mean ◽

Approximate Likelihood ◽

The One ◽

Mean Vector ◽

Critical Constants

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Conditional Likelihood Ratio Test for a Nonnegative Normal Mean Vector

Journal of the American Statistical Association ◽

10.1080/01621459.1998.10474119 ◽

1998 ◽

Vol 93 (441) ◽

pp. 380-386 ◽

Author(s):

Yining Wang ◽

Michael P. McDermott

Keyword(s):

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Conditional Likelihood ◽

Normal Mean ◽

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Asymptotic power comparison of T2-type test and likelihood ratio test for a mean vector based on two-step monotone missing data

Communication in Statistics- Theory and Methods ◽

10.1080/03610926.2019.1597122 ◽

2019 ◽

Vol 49 (17) ◽

pp. 4270-4287 ◽

Author(s):

Masashi Hyodo ◽

Nobumichi Shutoh

Keyword(s):

Missing Data ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Power Comparison ◽

Asymptotic Power ◽

Type Test ◽

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Corrections: Conditional Likelihood Ratio Test for a Nonnegative Normal Mean Vector

Journal of the American Statistical Association ◽

10.2307/2670215 ◽

1999 ◽

Vol 94 (446) ◽

pp. 660

Keyword(s):

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Conditional Likelihood ◽

Normal Mean ◽

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A likelihood ratio test for detecting patterns of disease-marker association

Annals of Human Genetics ◽

10.1017/s0003480097006349 ◽

1997 ◽

Vol 61 (4) ◽

pp. 335-350 ◽

Author(s):

A. P. MORRIS ◽

J. C. WHITTAKER ◽

R. N. CURNOW

Keyword(s):

Likelihood Ratio ◽

Likelihood Ratio Test ◽

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Supplemental Material for On the Likelihood Ratio Test in Structural Equation Modeling When Parameters Are Subject to Boundary Constraints

Psychological Methods ◽

10.1037/1082-989x.11.4.439.supp ◽

2006 ◽

Keyword(s):

Structural Equation Modeling ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Structural Equation ◽

Equation Modeling ◽

Boundary Constraints

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Faculty Opinions recommendation of A likelihood ratio test of speciation with gene flow using genomic sequence data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.3540959.3240060 ◽

2010 ◽

Author(s):

Nicolas Galtier ◽

Julien Dutheil

Keyword(s):

Gene Flow ◽

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Genomic Sequence ◽

Sequence Data ◽

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