Pardo Llorente, LeandroPardo Llorente, María del Carmen2023-06-202023-06-202008-01-01Ali, S.M., Silvey, S.D., 1966. A general class of coefficients of divergence of one distribution from another. J. R. Statist. Soc. Ser. B 26, 131–142. Bock, R.D., 1970. Estimating multinomial response relations. In: Bose, R.C. (Ed.),Contributions to Statistics and Probability. University of North Carolina Press, Chapel Hill, NC, pp. 453–479. Cressie, N., Read, T.R.C., 1984. Multinomial goodness-of-fit tests. J. R. Statist. Soc. Ser. B 46, 440–464. Csiszár, I., 1963. Eine Informationstheoretische Ungleichung und ihre Anwendung auf den Beweis der Ergodizität on Markhoffschen Ketten. Publ. Math. Inst. Hung. Acad. of Sci. Ser. A 8, 85–108. Dik, J.J., Gunst, M.C.M., 1985. The distribution of general quadratic forms in normal variables. Statistica Neerlandica 39 (1), 14–26. Gupta, A.K., Kasturiratna, D., Nguyen, T., Pardo, L., 2006a.Anewfamily of BANestimators in polytomous regression models based on-divergence measures. Statist. Methods Appl. 15, 159–176. Gupta, A.K., Nguyen, T., Pardo, L., 2006b. Some inference procedures in polytomous logistic regression models based on -divergences measures. Math. Methods Statist. 15 (3), 269–288. Haberman, S.J., 1974. The Analysis of Frequency Data. University of Chicago Press, Chicago. Liu, I., Agresti, A., 2005. The analysis of ordered categorical data: an overview and a survey of recent developments. Test 14 (1), 1–73. Mantel, N., 1966. Models for complex contingency tables and polychotomous dosage response curves. Biometrics 22, 83–95. Nerlove, M., Press, S.J., 1973. Univariate and multivariate log-linear and logistic models. Technical Report R-1306-EDA/NIH, Rand Corporation, Santa Monica, CA. Pardo, L., 2006. Statistical Inference Based on Divergence Measures Statistics: Textbooks and Monographs. Chapman & Hall/CRC, New York. Pardo, J.A., Pardo, L., Zografos, K., 2002. Minimum phi-divergence Estimator with constraints in multinomial populations. J. Statist. Plann. Inference 104, 221–237. Pardo, J.A., Pardo, L., Pardo, M.C., 2005. Minimum phi-divergence estimator in logistic regression model. Statist. Papers 47, 91–108. Theil, H., 1969. A multinomial extension of the linear logit model. Int. Econ. Rev. 10, 103–154. Theil, H., 1970. On the estimation of relationships involving qualitative variables. Am. J. Sociol. 76, 251–259. Vajda, I., 1989. Theory of Statistical Inference and Information. Kluwer Academic Publishers, Dordrecht.0167-9473http://0-dx.doi.org.cisne.sim.ucm.es/10.1016/j.csda.2007.04.007https://hdl.handle.net/20.500.14352/50262A new family of test statistics for testing linear hypotheses in baseline-category logit models is introduced and its asymptotic distribution is obtained. The new family is a natural extension of the classical likelihood ratio test. A simulation study is carried out to find new test statistics that offer an attractive alternative to the classical likelihood ratio test in terms of both exact size and exact power.engjournal articlehttp://www.sciencedirect.com/science/article/pii/S0167947307001600http://www.sciencedirect.com/restricted access519.233.5baseline-category logit modelextended likelihood ratio test statisticslinear hypothesesdivergnece.Estadística aplicada