Homogeneity test and sample size of risk difference for stratified unilateral and bilateral data

Sun, Shuman; Li, Zhiming; Jiang, Haijun

doi:10.1080/03610918.2022.2142240

Cited by 4 publications

(2 citation statements)

References 26 publications

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“…Qiu, Poon, Tang, and Tao (2019) presented five simultaneous CIs for risk differences in stratified bilateral designs and developed seven CIs for the common risk difference under the homogeneity assumption. Sun, Li, and Jiang (2022) proposed the homogeneity test of risk difference to determine the necessity of stratified treatment.…”

Section: Introductionmentioning

confidence: 99%

Testing the common risk difference of proportions for stratified uni‐ and bilateral correlated data

Mou

2023

Statistica Neerlandica

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In medical clinical studies, uni‐ and bilateral data naturally occurs if each patient contributes either one or both of paired organ measurements in a stratified design. This paper mainly proposes a common test of risk differences between proportions for stratified uni‐ and bilateral correlated data. Likelihood ratio, score, and Wald‐type test statistics are constructed using global, unconstrained, and constrained maximum likelihood estimations of parameters. Simulation studies are conducted to evaluate the performance of these test procedures in terms of type I error rates and powers. Empirical results show that the likelihood ratio test is more robust and powerful than other statistics. A real example is used to illustrate the proposed methods.

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Section: Introductionmentioning

confidence: 99%

Testing the common risk difference of proportions for stratified uni‐ and bilateral correlated data

Mou

2023

Statistica Neerlandica

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“…Further, Qiu et al [15] used an iterative algorithm to calculate the asymptotic sample sizes of common tests for binomial proportions. Sun et al [16] extended the iterative algorithm to the homogeneity test in stratified unilateral and bilateral data. For more detailed results of sample sizes, we refer to [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Asymptotic Sample Size for Common Test of Relative Risk Ratios in Stratified Bilateral Data

Mou,

Li,

2023

Mathematics

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In medical clinical studies, various tests usually relate to the sample size. This paper proposes several methods to calculate sample sizes for a common test of relative risk ratios in stratified bilateral data. Under the prespecified significant level and power, we derive some explicit formulae and an algorithm of the sample size. The sample sizes of the stratified intra-class model are obtained from the likelihood ratio, score, and Wald-type tests. Under pooled data, we calculate sample size based on the Wald-type test and its log-transformation form. Numerical simulations show that the proposed sample sizes have empirical power close to the prespecified value for given significance levels. The sample sizes from the iterative method are more stable and effective.

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Homogeneity Test and Sample Size Determination of Odds Ratios for Stratified Unilateral and Bilateral Paired Data

计

2024

AAM

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Homogeneity test and sample size of risk difference for stratified unilateral and bilateral data

Cited by 4 publications

References 26 publications

Testing the common risk difference of proportions for stratified uni‐ and bilateral correlated data

Testing the common risk difference of proportions for stratified uni‐ and bilateral correlated data

Asymptotic Sample Size for Common Test of Relative Risk Ratios in Stratified Bilateral Data

Homogeneity Test and Sample Size Determination of Odds Ratios for Stratified Unilateral and Bilateral Paired Data

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