Miao Huazhang

Mr. Miao Huazhang


Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 December 2015 in The International Journal of Biostatistics
Verified
Journal Article
Closed access
PDF file
MLMeng-Jie Lu
Meng-Jie Lu
WZWei-Hua Zhong
Wei-Hua Zhong
YLYu-Xiu Liu
Yu-Xiu Liu
MHMiao Huazhang
Miao Huazhang
YLYong-Chang Li
Yong-Chang Li
MJMuhuo Ji
Muhuo Ji
The Bland–Altman method has been widely used for assessing agreement between two methods of measurement. However, it remains unsolved about sample size estimation. We propose a new method of sample size estimation for Bland–Altman agreement assessment. According to the Bland–Altman method, the conclusion on agreement is made based on the width of the confidence interval for LOAs (limits of agreement) in comparison to predefined clinical agreement limit. Under the theory of statistical inference, the formulae of sample size estimation are derived, which depended on the pre-determined level of α , β, the mean and the standard deviation of differences between two measurements, and the predefined limits. With this new method, the sample sizes are calculated under different parameter settings which occur frequently in method comparison studies, and Monte-Carlo simulation is used to obtain the corresponding powers. The results of Monte-Carlo simulation showed that the achieved powers could coincide with the pre-determined level of powers, thus validating the correctness of the method. The method of sample size estimation can be applied in the Bland–Altman method to assess agreement between two methods of measurement.

8 August 2016 in Environmental Health
Verified
Journal Article
Open access
PDF file
ZLZhijiang Liang
Zhijiang Liang
YLYan Lin
Yan Lin
YMYuanzhu Ma
Yuanzhu Ma
LZLei Zhang
Lei Zhang
XZXue Zhang
Xue Zhang
QZQingguo Zhao
Qingguo Zhao
A few studies have examined the association between ambient temperature and preterm birth (PTB), and the results have been inconsistent. This study explored the association between ambient temperature and PTB in Shenzhen, China. Data of daily singleton PTB, air pollution and meteorological variables from 2005 to 2011 were collected in Shenzhen. A distributed lag non-linear model (DLNM) was used to investigate the association of the low and high temperatures (1st, 5th, 95th, and 99th percentiles) with PTB. The median temperature was 24.5 °C and the 1st, 5th, 95th, and 99th percentiles of daily mean temperatures were 9, 12.5, 29.9 and 30.7 °C, respectively. The prevalence of singleton PTB was 5.61 % in Shenzhen. The association between temperature and PTB was not linear. There was an immediate positive association of low temperature (1st and 5th percentiles) and a negative association of high temperature (95th and 99th percentiles) with PTB. The effect of low temperature 9 °C (1st) on PTB on the current day was stronger than that of 12.5 °C (5th), with a relative risk (RR) of 1.54 (95 % CI: 1.36–1.75) and 1.49 (95 % CI: 1.35–1.63), respectively. The cumulative RR (up to 30 days) of 9 and 12.5 °C was 1.72 (95 % CI: 1.28–2.33) and 1.96 (95 % CI: 1.60–2.39), respectively. The cumulative effects (up to 30 days) of high temperature (95th and 99th percentiles) on PTB were 0.69 (95 % CI: 0.60–0.80) and 0.62 (95 % CI: 0.52–0.74), respectively. The cumulative effect (up to 30 days) of low temperatures on vaginal delivery PTB was lower than that of the cesarean section PTB with an RR of 1.58 (95 % CI: 1.12–2.22) and 1.93 (95 % CI: 1.21–3.08), respectively. This study suggests that low temperature might be a risk factor, while high temperature might be a protective factor of PTB in Shenzhen.