On the Performance of a Test for Coefficient of Variation

Rao, K. Aruna; Vidya, R.

doi:10.1177/0008068319920106

Cited by 13 publications

(6 citation statements)

References 4 publications

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“…[8], and the Wald test statistic is [11]. The Wald Test statistic for the inverse-coefficients of variation has a chi-square distribution with ( − 1) degrees of freedom.…”

Section: Wald Testmentioning

confidence: 99%

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Testing the Population Inverse-Coefficients of Variation and Its Application

Potas

Gamgam

2019

Eskişehir Technical University Journal of Science and Technology a - Applied Sciences and Engineering

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In this paper, some tests are introduced and compared for testing the equality of inverse-coefficients of variation. Monte-Carlo simulation method is used for comparisons. In this simulation study, various simulation scenarios were designed with different population numbers (= 3, 6), sample sizes, parameter values and type I error rates (= 0.01, 0.05). The tests were compared in terms of type I error rate and power in these scenarios. When the sample sizes are small, the D and WT tests showed good results in terms of type I error, but the LR and ST tests did not give good results. As the sample sizes increased, the experimental type I error rates of the LR and ST tests converged to nominal type I error and all tests showed good results in general. While the sample sizes were equal, it was found that the LR test was the most powerful test and the ST test sometimes yielded good results. For these sample sizes, the D test yielded the worst results. When the sample sizes are different, the LR and D tests are powerful than the other tests, and the ST test is the worst test in terms of power. As expected, as the sample sizes and nominal type I error rate increased, the powers of the tests also increased. In addition, an application for the tests was made on real data. It was seen that the results of this application and simulation study coincide.

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“…[8], and the Wald test statistic is [11]. The Wald Test statistic for the inverse-coefficients of variation has a chi-square distribution with ( − 1) degrees of freedom.…”

Section: Wald Testmentioning

confidence: 99%

“…In Eqs. (11), is replaced by ̂, ̂ is obtained. For the inversecoefficients of variation, the Likelihood Ratio test statistic is −2 ln = ∑ ln (̂2 2 ) =1 ( 12) [9].…”

Section: Likelihood Ratio Testmentioning

confidence: 99%

Testing the Population Inverse-Coefficients of Variation and Its Application

Potas

Gamgam

2019

Eskişehir Technical University Journal of Science and Technology a - Applied Sciences and Engineering

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“…Nairy and Rao (2003) test. A meta-analytic test of k Ho : All   can also be constructed using equations appearing in Nairy and Rao (2003) that these authors attributed to Rao and Vidya (1992). Specifically,…”

Section: Meta-analytic Tests Of Kmentioning

confidence: 99%

An Effect Size for Variance Heterogeneity in Meta-Analysis

Harwell¹

2019

Proceedings of the 2019 AERA Annual Meeting

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The difference in two coefficients of variation is proposed as an effect size to capture variance heterogeneity for two groups across a sample of studies, and five tests of homogeneity of this effect size were studied. Capturing within-study differences in variability across a sample of studies should enhance understanding of treatment effects estimated by traditional mean-based effect sizes by providing information about the extent to which subjects in a treatment group responded similarly across studies relative to a control group. Monte Carlo results suggested the Miller-Feltz test can be used to test homogeneity of within-study variability.

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“…A modification of Bennett's method was provided by Shafer and Sullivan [7]. Wald tests have been introduced by [8][9][10]. Based on Renyi's divergence, Pardo and Pardo [11] proposed a new method.…”

Section: Introductionmentioning

confidence: 99%

Inference about the Ratio of the Coefficients of Variation of Two Independent Symmetric or Asymmetric Populations

Zhang

Băleanu

2019

Symmetry

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Coefficient of variation (CV) is a simple but useful statistical tool to make comparisons about the independent populations in many research areas. In this study, firstly, we proposed the asymptotic distribution for the ratio of the CVs of two separate symmetric or asymmetric populations. Then, we derived the asymptotic confidence interval and test statistic for hypothesis testing about the ratio of the CVs of these populations. Finally, the performance of the introduced approach was studied through simulation study.

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On the Performance of a Test for Coefficient of Variation

Cited by 13 publications

References 4 publications

Testing the Population Inverse-Coefficients of Variation and Its Application

Testing the Population Inverse-Coefficients of Variation and Its Application

An Effect Size for Variance Heterogeneity in Meta-Analysis

Inference about the Ratio of the Coefficients of Variation of Two Independent Symmetric or Asymmetric Populations

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