1.Impact of incorrect designation of working correlation structure matrix on sample size estimation in 2×2 cross design: a simulation study.
Peiyu ZHANG ; Ziheng XIE ; Yan ZHUANG
Journal of Southern Medical University 2025;45(11):2495-2503
OBJECTIVES:
To investigate the impact of incorrect specification of the working correlation structure matrix on estimated sample size in a 2×2 crossover design based on the generalized estimating equation (GEE).
METHODS:
Based on Monte Carlo simulation, the influence of incorrect specification of the work-related structure matrix on the sample size estimation under different conditions was evaluated after controlling the total sample size n, the proportion of subjects assigned to AB sequence (s=1) θ, the correlation coefficient ρ, and the placebo effect OR. Bias and mean square error (MSE) were used to assess the difference between the sample size estimates and the theoretical values.
RESULTS:
When the correctly specified working correlation structure matrix is independent, the sample size estimation effect of correctly specifying the working correlation structure matrix is better than that of incorrect specification. But when the correctly specified working correlation structure matrix is equal and the correlation coefficient is closer to 0, with other factors being smaller (n≤50, θ≤0.5, OR=2 in this article), there is a situation where the bias of the sample size estimation value for the correctly specified working correlation structure matrix is greater than the bias for the incorrectly specified working correlation structure matrix.
CONCLUSIONS
Under most conditions, incorrectly specifying the working correlation structure matrix can cause the estimated sample size to deviate significantly from the theoretical value, but under certain conditions, the impact of incorrectly specifying the working correlation structure matrix can be small on the estimated sample size.
Sample Size
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Monte Carlo Method
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Humans
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Cross-Over Studies
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Computer Simulation
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Research Design
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Bias
2.Landscape of respiratory syncytial virus.
Yuping DUAN ; Zimeng LIU ; Na ZANG ; Bingbing CONG ; Yuqing SHI ; Lili XU ; Mingyue JIANG ; Peixin WANG ; Jing ZOU ; Han ZHANG ; Ziheng FENG ; Luzhao FENG ; Lili REN ; Enmei LIU ; You LI ; Yan ZHANG ; Zhengde XIE
Chinese Medical Journal 2024;137(24):2953-2978
Respiratory syncytial virus (RSV) is an enveloped, negative-sense, single-stranded RNA virus of the Orthopneumovirus genus of the Pneumoviridae family in the order Mononegavirales. RSV can cause acute upper and lower respiratory tract infections, sometimes with extrapulmonary complications. The disease burden of RSV infection is enormous, mainly affecting infants and older adults aged 75 years or above. Currently, treatment options for RSV are largely supportive. Prevention strategies remain a critical focus, with efforts centered on vaccine development and the use of prophylactic monoclonal antibodies. To date, three RSV vaccines have been approved for active immunization among individuals aged 60 years and above. For children who are not eligible for these vaccines, passive immunization is recommended. A newly approved prophylactic monoclonal antibody, Nirsevimab, which offers enhanced neutralizing activity and an extended half-life, provides exceptional protection for high-risk infants and young children. This review provides a comprehensive and detailed exploration of RSV's virology, immunology, pathogenesis, epidemiology, clinical manifestations, treatment options, and prevention strategies.
Humans
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Respiratory Syncytial Virus Infections/prevention & control*
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Respiratory Syncytial Viruses/pathogenicity*
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Respiratory Syncytial Virus, Human/pathogenicity*
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Antiviral Agents/therapeutic use*

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