International Journal of Biostatistics最新文献_第5页

Cell Line Classification Using Electric Cell-Substrate Impedance Sensing (ECIS) 基于Cell- substrate Impedance Sensing (ECIS)的细胞系分类

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2017-10-26 DOI: 10.1515/ijb-2018-0083

Megan L. Gelsinger, Laura L. Tupper, D. Matteson

{"title":"Cell Line Classification Using Electric Cell-Substrate Impedance Sensing (ECIS)","authors":"Megan L. Gelsinger, Laura L. Tupper, D. Matteson","doi":"10.1515/ijb-2018-0083","DOIUrl":"https://doi.org/10.1515/ijb-2018-0083","url":null,"abstract":"Abstract We present new methods for cell line classification using multivariate time series bioimpedance data obtained from electric cell-substrate impedance sensing (ECIS) technology. The ECIS technology, which monitors the attachment and spreading of mammalian cells in real time through the collection of electrical impedance data, has historically been used to study one cell line at a time. However, we show that if applied to data from multiple cell lines, ECIS can be used to classify unknown or potentially mislabeled cells, factors which have previously been associated with the reproducibility crisis in the biological literature. We assess a range of approaches to this new problem, testing different classification methods and deriving a dictionary of 29 features to characterize ECIS data. Most notably, our analysis enriches the current field by making use of simultaneous multi-frequency ECIS data, where previous studies have focused on only one frequency; using classification methods to distinguish multiple cell lines, rather than simple statistical tests that compare only two cell lines; and assessing a range of features derived from ECIS data based on their classification performance. In classification tests on fifteen mammalian cell lines, we obtain very high out-of-sample predictive accuracy. These preliminary findings provide a baseline for future large-scale studies in this field.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":"16 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2017-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2018-0083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49126933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Combinatorial Mixtures of Multiparameter Distributions: An Application to Bivariate Data 多参数分布的组合混合：在双变量数据中的应用

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2017-02-16 DOI: 10.1515/ijb-2015-0064

V. Edefonti, G. Parmigiani

引用次数: 0

On Stratified Adjusted Tests by Binomial Trials 二项试验的分层校正检验

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2017-02-14 DOI: 10.1515/ijb-2016-0047

Asanao Shimokawa, E. Miyaoka

{"title":"On Stratified Adjusted Tests by Binomial Trials","authors":"Asanao Shimokawa, E. Miyaoka","doi":"10.1515/ijb-2016-0047","DOIUrl":"https://doi.org/10.1515/ijb-2016-0047","url":null,"abstract":"Abstract To estimate or test the treatment effect in randomized clinical trials, it is important to adjust for the potential influence of covariates that are likely to affect the association between the treatment or control group and the response. If these covariates are known at the start of the trial, random assignment of the treatment within each stratum would be considered. On the other hand, if these covariates are not clear at the start of the trial, or if it is difficult to allocate the treatment within each stratum, completely randomized assignment of the treatment would be performed. In both sampling structures, the use of a stratified adjusted test is a useful way to evaluate the significance of the overall treatment effect by reducing the variance and/or bias of the result. If the trial has a binary endpoint, the Cochran and Mantel-Haenszel tests are generally used. These tests are constructed based on the assumption that the number of patients within a stratum is fixed. However, in practice, the stratum sizes are not fixed at the start of the trial in many situations, and are instead allowed to vary. Therefore, there is a risk that using these tests under such situations would result in an error in the estimated variation of the test statistics. To handle the problem, we propose new test statistics under both sampling structures based on multinomial distributions. Our proposed approach is based on the Cochran test, and the difference between the two tests tends to have similar values in the case of a large number of patients. When the total number of patients is small, our approach yields a more conservative result. Through simulation studies, we show that the new approach could correctly maintain the type I error better than the traditional approach.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2017-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2016-0047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44587325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Testing Equality of Treatments under an Incomplete Block Crossover Design with Ordinal Responses 具有顺序响应的不完全块体交叉设计下处理平等性的检验

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2017-02-03 DOI: 10.1515/ijb-2016-0069

K. Lui

引用次数: 2

Bayesian Variable Selection Methods for Matched Case-Control Studies 匹配病例对照研究的贝叶斯变量选择方法

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2017-01-31 DOI: 10.1515/ijb-2016-0043

J. Asafu-Adjei, M. Tadesse, B. Coull, R. Balasubramanian, M. Lev, L. Schwamm, R. Betensky

引用次数: 5

Joint Model for Mortality and Hospitalization 死亡率和住院率联合模型

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2016-11-01 DOI: 10.1515/ijb-2016-0002

Yuqi Chen, Wensheng Guo, P. Kotanko, L. Usvyat, Yuedong Wang

{"title":"Joint Model for Mortality and Hospitalization","authors":"Yuqi Chen, Wensheng Guo, P. Kotanko, L. Usvyat, Yuedong Wang","doi":"10.1515/ijb-2016-0002","DOIUrl":"https://doi.org/10.1515/ijb-2016-0002","url":null,"abstract":"Abstract: Modeling hospitalization is complicated because the follow-up time can be censored due to death. In this paper, we propose a shared frailty joint model for survival time and hospitalization. A random effect semi-parametric proportional hazard model is assumed for the survival time and conditional on the follow-up time, hospital admissions or total length of stay is modeled by a generalized linear model with a nonparametric offset function of the follow-up time. We assume that the hospitalization and the survival time are correlated through a latent subject-specific random frailty. The proposed model can be implemented using existing software such as SAS Proc NLMIXED. We demonstrate the feasibility through simulations. We apply our methods to study hospital admissions and total length of stay in a cohort of patients on hemodialysis. We identify age, albumin, neutrophil to lymphocyte ratio (NLR) and vintage as significant risk factors for mortality, and age, gender, race, albumin, NLR, pre-dialysis systolic blood pressure (preSBP), interdialytic weight gain (IDWG) and equilibrated Kt/V (eKt/V) as significant risk factors for both hospital admissions and total length of stay. In addition, hospitalization admissions is positively associated with vintage.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":"12 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2016-0002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66988069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of Smoothing in Generalized Linear Mixed Models on the Estimation of Covariance Parameters for Longitudinal Data 广义线性混合模型中平滑对纵向数据协方差参数估计的影响

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2016-11-01 DOI: 10.1515/ijb-2015-0026

M. Mullah, A. Benedetti

{"title":"Effect of Smoothing in Generalized Linear Mixed Models on the Estimation of Covariance Parameters for Longitudinal Data","authors":"M. Mullah, A. Benedetti","doi":"10.1515/ijb-2015-0026","DOIUrl":"https://doi.org/10.1515/ijb-2015-0026","url":null,"abstract":"Abstract Besides being mainly used for analyzing clustered or longitudinal data, generalized linear mixed models can also be used for smoothing via restricting changes in the fit at the knots in regression splines. The resulting models are usually called semiparametric mixed models (SPMMs). We investigate the effect of smoothing using SPMMs on the correlation and variance parameter estimates for serially correlated longitudinal normal, Poisson and binary data. Through simulations, we compare the performance of SPMMs to other simpler methods for estimating the nonlinear association such as fractional polynomials, and using a parametric nonlinear function. Simulation results suggest that, in general, the SPMMs recover the true curves very well and yield reasonable estimates of the correlation and variance parameters. However, for binary outcomes, SPMMs produce biased estimates of the variance parameters for high serially correlated data. We apply these methods to a dataset investigating the association between CD4 cell count and time since seroconversion for HIV infected men enrolled in the Multicenter AIDS Cohort Study.","PeriodicalId":50333,"journal":{"name":"International Journal of Biostatistics","volume":"59 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2015-0026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66987691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Binomial Integer-Valued ARCH Model 二项整数值ARCH模型

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2016-11-01 DOI: 10.1515/ijb-2015-0051

M. Ristić, C. Weiß, Ana D Janjić

引用次数: 24

Testing Equality in Ordinal Data with Repeated Measurements: A Model-Free Approach 用重复测量检验有序数据的相等性:一种无模型方法

IF 1.2 4区数学

International Journal of Biostatistics Pub Date : 2016-11-01 DOI: 10.1515/ijb-2015-0075

K. Lui

引用次数: 1

A Comparison of Some Approximate Confidence Intervals for a Single Proportion for Clustered Binary Outcome Data 聚类二值结果数据单比例近似置信区间的比较