International journal of clinical biostatistics and biometrics最新文献

{"title":"Improved Wald Test for Equivalence Assessment of Analytical Biosimilarity","authors":"Wen Yu-ting, Tsong Yi, Shen Meiyu, W. Chao","doi":"10.23937/2469-5831/1510016","DOIUrl":"https://doi.org/10.23937/2469-5831/1510016","url":null,"abstract":"Citation: Yu-Ting Weng, Tsong Y, Shen M, Wang C (2018) Improved Wald Test for Equivalence Assessment of Analytical Biosimilarity. Int J Clin Biostat Biom 4:016. doi.org/10.23937/2469-5831/1510016 Received: September 29, 2017: Accepted: March 13, 2018: Published: March 15, 2018 Copyright: © 2018 Yu-Ting Weng, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75762509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Partial Variable Selection and its Applications in Biostatistics","authors":"Gu Jingwen, Yuan Ao, Zhou Chunxiao, Chan Leighton, Tan Ming T","doi":"10.23937/2469-5831/1510017","DOIUrl":"https://doi.org/10.23937/2469-5831/1510017","url":null,"abstract":"We propose and study a method for partial covariates selection, which only select the covariates with values fall in their effective ranges. The coefficients estimates based on the resulting data is more interpretable based on the effective covariates. This is in contrast to the existing method of variable selection, in which some variables are selected/deleted in whole. To test the validity of the partial variable selection, we extended the Wilks theorem to handle this case. Simulation studies are conducted to evaluate the performance of the proposed method, and it is applied to a real data analysis as illustration.","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76792013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian Cox Proportional Hazards Model in Survival Analysis of HACE1 Gene with Age at Onset of Alzheimer's Disease.","authors":"Ke-Sheng Wang,&nbsp;Ying Liu,&nbsp;Shaoqing Gong,&nbsp;Chun Xu,&nbsp;Xin Xie,&nbsp;Liang Wang,&nbsp;Xingguang Luo","doi":"10.23937/2469-5831/1510014","DOIUrl":"https://doi.org/10.23937/2469-5831/1510014","url":null,"abstract":"<p><p>Alzheimer's disease (AD), the most common form of dementia, is a chronic neurodegenerative disease. The HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1) gene is expressed in human brain and may play a role in the pathogenesis of neurodegenerative disorders. Till now, no previous study has reported the association of the HACE1 gene with the risk and age at onset (AAO) of AD; while few studies have checked the proportional hazards assumption in the survival analysis of AAO of AD using Cox proportional hazards model. In this study, we examined the associations of 14 single nucleotide polymorphisms (SNPs) in the HACE1 gene with the risk and the AAO of AD using 791 AD patients and 782 controls. Multiple logistic regression model identified one SNP (rs9499937 with p = 1.8×10^-3) to be associated with the risk of AD. For survival analysis of AAO, both classic Cox regression model and Bayesian survival analysis using the Cox proportional hazards model were applied to examine the association of each SNP with the AAO. The hazards ratio (HR) with its 95% confidence interval (CI) was estimated. Survival analysis using the classic Cox regression model showed that 4 SNPs were significantly associated with the AAO (top SNP rs9499937 with HR=1.33, 95%CI=1.13-1.57, p=5.0×10^-4). Bayesian Cox regression model showed similar but a slightly stronger associations (top SNP rs9499937 with HR=1.34, 95%CI=1.11-1.55) compared with the classic Cox regression model. Using an independent family-based sample, one SNP rs9486018 was associated with the risk of AD (p=0.0323) and the T-T-G haplotype from rs9786015, rs9486018 and rs4079063 showed associations with both the risk and AAO of AD (p=2.27×10^-3 and 0.0487, respectively). The findings of this study provide first evidence that several genetic variants in the HACE1 gene were associated with the risk and AAO of AD.</p>","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.23937/2469-5831/1510014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35820772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychophysiological Differences in Patients with/without Schizophrenia: A Comparative Study","authors":"Antonis Theofilidis, K. Fountoulakis","doi":"10.23937/2469-5831/1510034","DOIUrl":"https://doi.org/10.23937/2469-5831/1510034","url":null,"abstract":"","PeriodicalId":91282,"journal":{"name":"International journal of clinical biostatistics and biometrics","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85566368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}