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An optimized industry processing technology of peanut tofu and the novel prediction model for suitable peanut varieties 期刊论文
JOURNAL OF INTEGRATIVE AGRICULTURE, 2020, 卷号: 19, 期号: 9, 页码: 2340-2351
Authors:  Chen Bing-yu;  Li Qi-zhai;  Hu Hui;  Meng Shi;  Shah, Faisal;  Wang Qiang;  Liu Hong-zhi
Favorite  |  View/Download：27/0  |  Submit date：2020/09/23
peanut tofu  process  quality  peanut variety selection  evaluation standard  prediction model  
Nonparametric estimation of distributions and diagnostic accuracy based on group-tested results with differential misclassification 期刊论文
BIOMETRICS, 2020, 页码: 10
Authors:  Zhang, Wei;  Liu, Aiyi;  Li, Qizhai;  Albert, Paul S.
Favorite  |  View/Download：7/0  |  Submit date：2020/10/12
coverage probability  diagnostic accuracy  differential misclassification  group testing  integrated absolute bias  integrated mean squared error  rare disease  ROC curves  
A cluster-adjusted rank-based test for a clinical trial concerning multiple endpoints with application to dietary intervention assessment 期刊论文
BIOMETRICS, 2019, 卷号: 75, 期号: 3, 页码: 821-830
Authors:  Zhang, Wei;  Liu, Aiyi;  Tang, Larry L.;  Li, Qizhai
Favorite  |  View/Download：23/0  |  Submit date：2020/01/10
generalized Behrens-Fisher hypothesis  multivariate distributions  nonparametrics  rank statistics  type I errors  power of test  
A Powerful Method To Test Associations Between Ordinal Traits and Genotypes 期刊论文
G3-GENES GENOMES GENETICS, 2019, 卷号: 9, 期号: 8, 页码: 2573-2579
Authors:  Wang, Jinjuan;  Ding, Juan;  Huang, Shouyou;  Li, Qizhai;  Pan, Dongdong
Favorite  |  View/Download：21/0  |  Submit date：2020/01/10
association study  ordinal phenotype  latent normal variate  generalized estimating equation  M-estimation  
A theoretic study of a distance-based regression model 期刊论文
SCIENCE CHINA-MATHEMATICS, 2019, 卷号: 62, 期号: 5, 页码: 979-998
Authors:  Li, Jialu;  Zhang, Wei;  Zhang, Sanguo;  Li, Qizhai
Favorite  |  View/Download：28/0  |  Submit date：2020/01/10
distance-based regression  Euclidean  pseudo F test statistic  Mahalanobis  
A powerful test for ordinal trait genetic association analysis 期刊论文
STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY, 2019, 卷号: 18, 期号: 2, 页码: 9
Authors:  Xue, Yuan;  Wang, Jinjuan;  Ding, Juan;  Zhang, Sanguo;  Li, Qizhai
Favorite  |  View/Download：22/0  |  Submit date：2020/01/10
ordinal response  power  proportional odds model  response selective sampling  
Improved matrix pooling 期刊论文
STATISTICAL METHODS IN MEDICAL RESEARCH, 2019, 卷号: 28, 期号: 1, 页码: 211-222
Authors:  Xiong, Wenjun;  Ding, Juan;  He, Yuanzhen;  Li, Qizhai
Favorite  |  View/Download：25/0  |  Submit date：2019/03/05
Matrix pooling  efficiency  group testing  sensitivity  specificity  
Economic Transition and Changing Location of Manufacturing Industry in China: A Study of the Yangtze River Delta 期刊论文
SUSTAINABILITY, 2018, 卷号: 10, 期号: 8, 页码: 28
Authors:  Wu, Jiawei;  Wei, Yehua Dennis;  Li, Qizhai;  Yuan, Feng
Favorite  |  View/Download：29/0  |  Submit date：2018/11/16
globalization  industrial location  GW-SSM  Yangtze River Delta  China  
A regulatory insertion-deletion polymorphism in the FADS gene cluster influences PUFA and lipid profiles among Chinese adults: a population-based study 期刊论文
AMERICAN JOURNAL OF CLINICAL NUTRITION, 2018, 卷号: 107, 期号: 6, 页码: 867-875
Authors:  Li, Peiqin;  Zhao, Jing;  Kothapalli, Kumar S. D.;  Li, Xiang;  Li, Hui;  Han, Yuxuan;  Mi, Shengquan;  Zhao, Wenhua;  Li, Qizhai;  Zhang, Hong;  Song, Yiqing;  Brenna, J. Thomas;  Gao, Ying
Favorite  |  View/Download：29/0  |  Submit date：2018/07/30
dyslipidemia  gene polymorphism  fatty acid desaturases  insertion-deletion  long-chain polyunsaturated fatty acids  
Evaluating the Accuracy of Small P-Values In Genetic Association Studies Using Edgeworth Expansions 期刊论文
SCANDINAVIAN JOURNAL OF STATISTICS, 2018, 卷号: 45, 期号: 1, 页码: 1-33
Authors:  Zheng, Gang;  Xiong, Jinghong;  Li, Qizhai;  Xu, Jinfeng;  Yuan, Ao;  Gastwirth, Joe L.
Favorite  |  View/Download：24/0  |  Submit date：2018/07/30
chi-squared test  Edgeworth expansion  maximin efficiency robust test (MERT)  maximum likelihood estimate  nuisance parameter