A Score Test Against One-Sided Alternatives

Silvapulle, Mervyn J.; Silvapulle, Paramsothy

doi:10.2307/2291159

Cited by 46 publications

(45 citation statements)

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“…If the interest is to assess the hypothesis H : r 0 against A : r ! 0, with at least one strict inequality in A, we may show, by using similar calculations of those given in Section 3, that the score-type test proposed by Silvapulle and Silvapulle (1995) takes here the following form:…”

Section: :2 Experiments With Rotifersmentioning

confidence: 69%

“…Let us define the vector q H b T ; 0 T and consider G bb , G br , G rb and G rr as a partition of G to conform with q b T ; r T . From Silvapulle and Silvapulle (1995) we define the statistics…”

Section: One-sided Testmentioning

confidence: 99%

“…The additional requirement in the Appendix demonstrations is that k j 3 I, Vj, where k j denotes the number of groups with intracluster correlation r j and k k 1 Á Á Á k q . Then, it follows from Silvapulle and Silvapulle (1995) that the limit distribution of T S , under H, is a mixture of chi-square distributions, namely T S 3 h w 0 q; A rr c 2 0 w 1 q; A rr c 2 1 Á Á Á w q q; A rr c 2 q , where w`q; A rr 's are known as level probabilities (see definition and expressions, for instance, in Shapiro, 1985), which are expressed as functions of correlation coefficients associated with the matrix A rr , that is here a q Â q matrix. These correlation coefficients are the minimum information necessary to compute the asymptotic null distribution of T S because w`q; A rr depends on A rr only through its correlation matrix.…”

Section: :2 Experiments With Rotifersmentioning

confidence: 99%

See 2 more Smart Citations

One-Sided Test to Assess Correlation in Linear Logistic Models using Estimating Equations

Paula

Artes

2000

Biom. J.

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Section: :2 Experiments With Rotifersmentioning

confidence: 69%

Section: One-sided Testmentioning

confidence: 99%

Section: :2 Experiments With Rotifersmentioning

confidence: 99%

See 1 more Smart Citation

One-Sided Test to Assess Correlation in Linear Logistic Models using Estimating Equations

Paula

Artes

2000

Biom. J.

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“…In this setting, Sen (1984), and the same test was proposed by Silvapulle (1994) and Silvapulle and Silvapulle (1995) using a different rationale. …”

Section: Proportional Hazards Models: Ungrouped Datamentioning

confidence: 99%

“…We now relate this test to that proposed by Silvapulle (1994) and Silvapulle and Silvapulle (1995). Given the distance determined by the inner product (a, b)z = a'Eb and a closed, convex set C, the projection of a onto C is denoted by zrz(a [ C) and it…”

Section: Score Testsmentioning

confidence: 99%

Testing order restricted hypotheses with proportional hazards

Singh¹,

Wright²

1996

Lifetime Data Anal

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Inferences for survival curves based on right censored continuous or grouped data are studied. Testing homogeneity with an ordered restricted alternative and testing the order restriction as the null hypothesis are considered. Under a proportional hazards model, the ordering on the survival curves corresponds to an ordering on the regression coefficients. Approximate likelihood methods are obtained by applying order restricted procedures to the estimates of the regression coefficients. Ordered analogues to the log rank test which are based on the score statistics are considered also. Chi-bar-squared distributions, which have been studied extensively, are shown to provide reasonable approximations to the null distributions of these tests statistics. Using Monte Carlo techniques, the powers of these two types of tests are compared with those that are available in the literature.

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A transformed random effects model with applications

Yang

Huang

2009

Appl. Stochastic Models Bus. Ind.

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This paper proposes a transformed random effects model for analyzing non-normal panel data where both the response and (some of) the covariates are subject to transformations for inducing flexible functional form, normality, homoscedasticity and simple model structure.We develop maximum likelihood procedure for model estimation and inference, along with a computational devise which makes the estimation procedure feasible in cases of large panels. We give model specification tests which take into account the fact that parameter values for error components cannot be negative. We illustrate the model and methods with two applications: state production and wage distribution. The empirical results strongly favor the new model to the standard ones where either linear or log-linear functional form is employed. Monte Carlo simulation shows that maximum likelihood inference is quite robust against mild departure from normality.

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A Score Test Against One-Sided Alternatives

Cited by 46 publications

References 0 publications

One-Sided Test to Assess Correlation in Linear Logistic Models using Estimating Equations

One-Sided Test to Assess Correlation in Linear Logistic Models using Estimating Equations

Testing order restricted hypotheses with proportional hazards

A transformed random effects model with applications

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