• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.109-117
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• 2023

Intuitively, a test with more assumptions has greater power than a test with fewer assumptions. This kind of examples are abundant in the nonparametric tests vs corresponding parametric ones. In general, the nonparametric tests are less efficient in terms of asymptotic relative efficiency (ARE) compared to corresponding parametric tests (Daniel, 1990). However, this is not always true. To test equal means under independent normal samples, the usual test involves using the t-distribution with the pooled estimator of the common variance. Adding the assumption of equal sample size, we may derive another test. In this case, two tests using more assumptions were performed for univariate (multivariate) cases. For these examples, it was found that the power function of a test with more assumptions is less than or equal to that of a test with fewer assumptions. This finding can be used as an expository example in master's mathematical statistics courses.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.11-22
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• 2014

In this study, we propose a simultaneous test procedure based on the individual - values for each sub-null hypothesis with several well-known combining functions. We then compare the efficiency of our procedure with existing tests by obtaining empirical powers through a simulation study. Finally, we discuss some interesting features related to simultaneous test and point out a misconduct for the simulation study published in the previous work.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.353-359
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• 2003

This paper deals with the problem of testing mean change with one change-point with the normal random variables. We propose a test with the mean difference for change in a location parameter. A power comparison study of various change-point test statistics is performed via Monte Carlo simulation with S-plus software.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.195-204
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• 1996

Some rank tests for comparing r treatments against ordered alternatives are proposed when some of data are randomly cemsored, which are the weighted logrank tests based on pairwise-ranking scheme. The covariances of the proposed test statistics are explicitly obtained from the results of the counting process theory and the test procedures are illustrated by a numerical example. Simulation studies are also performed for comparing with the other well-known tests.

• International Journal of Reliability and Applications
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• v.1 no.1
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• pp.39-47
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• 2000

In a resent paper, Na and Kim(2000) develop a family of test statistics for testing whether or not the mean residual life changes its trend based on complete data and show that the new tests perform better than previously known tests. In this paper, we extend their tests to the randomly censored data. The asymptotic normality of the test statistics is established. Monte Carlo simulations are conducted to compare our tests with a previously known test by the power of tests.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.213-220
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• 1995

We consider a class of the weighted logrank tests and 4 types of weights in this class. We propese a test based on the maximum of 4 weighted logrank statistics and suggest a simulation techniqur to obtain the p-value of proposed test. It is shown through the simulation studies that the proposed test is robust and has reasonably good powers comparing with the well known efficient tests.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.453-465
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• 1997

The family of power-divergence statistics conditional on margins is considered for testing homogeneity of .tau. multinomial populations with equal sample size and the exact Bahadur slope is obtained. It is shown that the likelihood ratio test conditional on margins is the most Bahadur efficient among the family of power-divergence statistics.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.373-384
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• 2003

In this paper, we formulate multivariate one-sided alternatives and propose a class of nonparametric tests for possibly right censored data. We obtain the asymptotic tail probability (or p-value) by showing that our proposed test statistics have asymptotically multivariate normal distributions. Also, we illustrate our procedure with an example and compare it with other procedures in terms of empirical powers for the bivariate case. Finally, we discuss some properties of our test.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.163-168
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• 2009

Given the specific mean shift outlier model, the standard approaches to obtaining test statistics for outliers are discussed. Accuracy of outlier tests is investigated using subset curvatures. These subset curvatures appear to be reliable indicators of the adequacy of the linearization based test. Also, we consider obtaining graphical summaries of uncertainty in estimating parameters through confidence curves. The results are applied to the problem of assessing the accuracy of outlier tests.

• Journal of Korean Society for Quality Management
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• v.15 no.2
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• pp.38-49
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• 1987

Experimenters often want to test whether a specific treatment is really better than the others. In such a problem we derive the likelihood ratio test and compare the result with other multiple comparisons procedures. A nonparametric procedure based on ranks is also considered. Pitman efficiency of the rank-sum procedure relative to the likelihood ratio test is computed.