On the Relationship between Pearson Correlation Coefficient and Kendall’s Tau under Bivariate Homogeneous Shock Model

Wang, Jiantian

doi:10.5402/2012/717839

Cited by 8 publications

(3 citation statements)

References 10 publications

(1 reference statement)

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“…The calculated ICC is greater than the corresponding Kendall's τ, and ICC reaches its theoretical upper limit of 1 when τ is roughly 0.73 in our simulations. The calculated ICC and the corresponding Kendall's τ under our simulation settings agree with both the Capéraà-Genest inequality ICC ≥ τ ≥ 0 58,59 and the Daniels inequality |2ICC − 3τ| ≤ 1. 58,60 Figure 1 shows the non-linear relationship between Kendall's τ and calculated ICC (ICC >1 is not shown).…”

Section: Frailty Modelsupporting

confidence: 80%

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Simulating time-to-event data subject to competing risks and clustering: A review and synthesis

Meng

Esserman

et al. 2022

Stat Methods Med Res

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Simulation studies play an important role in evaluating the performance of statistical models developed for analyzing complex survival data such as those with competing risks and clustering. This article aims to provide researchers with a basic understanding of competing risks data generation, techniques for inducing cluster-level correlation, and ways to combine them together in simulation studies, in the context of randomized clinical trials with a binary exposure or treatment. We review data generation with competing and semi-competing risks and three approaches of inducing cluster-level correlation for time-to-event data: the frailty model framework, the probability transform, and Moran’s algorithm. Using exponentially distributed event times as an example, we discuss how to introduce cluster-level correlation into generating complex survival outcomes, and illustrate multiple ways of combining these methods to simulate clustered, competing and semi-competing risks data with pre-specified correlation values or degree of clustering.

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Section: Frailty Modelsupporting

confidence: 80%

“…The calculated ICC and the corresponding Kendall's τ under our simulation settings agree with both the Capéraà-Genest inequality ICC ≥ τ ≥ 0 58,59 and the Daniels inequality |2ICC − 3τ| ≤ 1. 58,60 Figure 1 shows the non-linear relationship between Kendall's τ and calculated ICC (ICC >1 is not shown).…”

Section: Frailty Modelsupporting

confidence: 80%

Simulating time-to-event data subject to competing risks and clustering: A review and synthesis

Meng

Esserman

et al. 2022

Stat Methods Med Res

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“…There are criteria to determine the degree of strength of the relationship between variables based on interpreting the correlation coefficient. The condition, refers to the absolute value of the correlation (r) as a simple rule, is 0 < |r| <0.49: weak relationship, 0.50 < |r| <0.79: moderate relationship, and 0.80 < |r| <1: strong relationship [69,70]. Below is the standard for determining the alternative hypothesis and the null hypothesis.…”

Section: -2-model Assessmentmentioning

confidence: 99%

Using Correlation to Explore the Impact of Corona Virus Disease on Socioeconomics

Fitriadi

Jiuhardi²,

Busari³

et al. 2022

Emerg Sci J

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In the 21stcentury, the tragedy of the pandemic shocks the world. This non-natural disaster is called COVID-19. Its dominant effect is also worrying about social and economic conflicts at local, national, and even international levels. The orientation of this research is to investigate the impact of COVID-19 on the socioeconomic aspects in Indonesia from 2020-2022. We set the research using official/secondary publications. Data analysis was interpreted in three formats: Pearson, Kendall’s, and Spearman’s correlations. It channelled empirical testing through Microsoft Excel and SPSS v.25. Social items include migration, mortality, domestic violence, and sexual harassment, while the nine economic items are per capita spending, well-being, unemployment, poverty, and labor productivity. Then, statistical instruments were reviewed based on the correlation coefficient and level of significance (5% for Pearson and 1% for Kendall’s and Spearman’s). The results are not much different between Pearson’s approach, Kendall’s and Spearman’s. In Pearson model, it proved a negative correlation when COVID-19 increases, so migration, unemployment, poverty, and labor productivity decrease. COVID-19 has had a positive impact on mortality, domestic violence, sexual harassment, per capita spending, and well-being. In Kendall’s and Spearman’s tests, poverty and labor productivity have actually increased because of COVID-19. Implementing semi-lockdown is a priority so that the social and macroeconomic constellations continue without ignoring the latent dangers of COVID-19. The limitations of the study are discussed in the future. Doi: 10.28991/esj-2022-SPER-012 Full Text: PDF

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Water Quality Index Is an Important Tool of Groundwater: A Case Study

Das

Roy

Banerjee

et al. 2021

Lecture Notes in Civil Engineering

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On the Relationship between Pearson Correlation Coefficient and Kendall’s Tau under Bivariate Homogeneous Shock Model

Cited by 8 publications

References 10 publications

Simulating time-to-event data subject to competing risks and clustering: A review and synthesis

Simulating time-to-event data subject to competing risks and clustering: A review and synthesis

Using Correlation to Explore the Impact of Corona Virus Disease on Socioeconomics

Water Quality Index Is an Important Tool of Groundwater: A Case Study

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