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2015 | 52 | 2 | 95-104
Tytuł artykułu

Power comparison of Rao′s score test, the Wald test and the likelihood ratio test in (2xc) contingency tables

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
There are several statistics for testing hypotheses concerning the independence of the distributions represented by two rows in contingency tables. The most famous are Rao′s score, the Wald and the likelihood ratio tests. A comparison of the power of these tests indicates the Wald test as the most powerful.
Wydawca
Czasopismo
Rocznik
Tom
52
Numer
2
Strony
95-104
Opis fizyczny
Daty
wydano
2015-12-01
online
2015-12-12
Twórcy
autor
  • Department of Mathematical and Statistical Methods, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland, andobek@up.poznan.pl
  • Department of Mathematical and Statistical Methods, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland
  • Department of Mathematical and Statistical Methods, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland
Bibliografia
  • Chandra T.K., Joshi S.N. (1983): Comparison of likelihood ratio, Rao’s and Wald’s tests and a conjecture of C.R. Rao. Sankhya A, 45: 226-246.
  • Fox J. (1997): Applied regression analysis, linear models, and related methods. Thousand Oaks, CA, US: Sage Publications, Inc.
  • Li B. (2001): Sensitivity of Rao’s score test, the Wald test and the likelihood ratio test to nuisance parameters. J. Statistical Planning and Inference 97: 57-66.
  • Madansky A. (1989): A comparison of the Likelihood Ratio, Wald, and Rao tests. In: Contributions to Probability and Statistics, I.J. Gleser et al. (eds.), Springer, New York: 465-471.
  • Neyman J., Pearson E.S. (1928): On the use and interpretation of certain test criteria. Biometrika 20A: 175-240.
  • Peers H.W. (1971): Likelihood ratio and associated test criteria. Biometrika 58: 577-587.[Crossref]
  • R Core Team (2013): R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.Rproject. org/.
  • Rao C.R. (1948): Large sample tests of statistical hypotheses concerning several parameters with application to problems of estimation. Proccedings of the Cambridge Philosophical Society 44: 50-57.
  • Rao C.R. (2005): Score test: historical review and recent developments. Advances in Ranking and Selection, Multiple Comparisons and Reliability. In: Statistics for Industry and Technology, Balakrishnan N., Kannan N., Nagaraja H.N. (eds.): 3-20.
  • Sutradhar B.C., Bartlett R.F. (1993a): Monte Carlo comparison of Wald’s, likelihood Ratio and Rao’s tests. J.Statist. Comput. Simul. 46: 23-33.
  • Sutradhar B.C., Bartlett R.F. (1993b): A small and large sample comparison of Wald’s, Likelihood Ratio and Rao’s tests for testing linear regression with autocorrelated errors. Sankhya: The Indian Journal of Statistics 55 B: 186-198.
  • Wald A. (1943): Tests of statistical hypotheses concerning several parameters when the number of observations is large. Transactions of the American Mathematical Society 54: 426-482.
  • Yi Y., Wang X. (2011): Comparison of Wald, Score, and Likelihood Ratio Tests for Response Adaptive Designs. J. Statistical Theory and Applications 10(4): 553-569.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.doi-10_1515_bile-2015-0009
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