检索结果-内蒙古大学图书馆

Detection of Cooperative Interactions in logistic regression models

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2017年第7期65卷 1765-1780页

作者： Xu, Easton Li Qian, Xiaoning Liu, Tie Cui, Shuguang Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA Univ Calif Davis Dept Elect & Comp Engn Davis CA 95616 USA

An important problem in the field of bioinformatics is to identify interactive effects among profiled variables for outcome prediction. In this paper, a logistic regression model with pairwise interactions among a set of binary covariates is considered. modeling the structure of the interactions by a graph, our goal is to recover the interaction graph from independently identically distributed (i.i.d.) samples of the covariates and the outcome. When viewed as a feature selection problem, a simple quantity called influence is proposed as a measure of the marginal effects of the interaction terms on the outcome. For the case when the underlying interaction graph is known to be acyclic, it is shown that a simple algorithm that is based on a maximum-weight spanning tree with respect to the plug-in estimates of the influences not only has strong theoretical performance guarantees, but can also outperform generic feature selection algorithms for recovering the interaction graph from i.i.d. samples of the covariates and the outcome. Our results can also be extended to the model that includes both individual effects and pairwise interactions via the help of an auxiliary covariate.

关键词： logistic regression model structure learning feature selection pairwise interaction

来源：评论

学校读者我要写书评

暂无评论

An evaluation of logistic regression models for predicting amphipod toxicity from sediment chemistry

引用

ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2005年第10期24卷 2691-2700页

作者： Wetherington, JD Stanley, BH Adams, KO Schwer, RE URS Diamond DuPont Corp Remediat Grp Wilmington DE 19805 USA DuPont Crop Protect Newark DE 19711 USA Writing Unltd Contract DuPont Corp Remediat Grp Wilmington DE 19805 USA DuPont Engn Technol Wilmington DE 19898 USA

An empirical screening level approach was developed to assess the probability of toxicity to benthic organisms associated with contaminated sediment exposure. The study was based on simple logistic regression models (LRMs) of matching sediment chemistry and toxicity data retrieved from a large database of field-collected sediment samples contaminated with multiple chemicals. Three decisions were made to simplify the application of LRMs to sediment samples contaminated with multiple chemicals. First, percent mortality information associated with each sediment sample was condensed into a dichotomous response (i.e., toxic or nontoxic). Second, each LRM assumed that toxicity was attributable to a single contaminant. Third, individual contaminants present at low concentrations were excluded from toxic sediment samples. Based on an analysis of the National Sediment Inventory database, the LRM approach classified 55% of nontoxic sediments as toxic (i.e., false-positives). Because this approach has been used to assess the probability of benthic toxicity as reported by the U.S. Environmental Protection Agency (U.S. EPA), the resultant estimates of potential toxicity convey a misleading impression of the increased hazard that sediments pose to the health of aquatic organisms at many sites in the United States. This could result in important resources needlessly being diverted from truly contaminated sites to evaluate and possibly remediate sediments at uncontaminated sites.

关键词： benthic toxicity sediment logistic regression model synergism

来源：评论

学校读者我要写书评

暂无评论

Phi-divergence statistics for testing linear hypotheses in logistic regression models

引用

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2008年第4期37卷 494-507页

作者： Menendez, Maria Luisa Pardo, Julio Angel Pardo, Leandro Univ Complutense Madrid Dept Stat & Operat Res 1 Madrid 28040 Spain Teeh Univ Madrid ETSAM Dept Appl Mathemat Madrid Spain

In this paper we introduce and study two new families of statistics for the problem of testing linear combinations of the parameters in logistic regression models. These families are based on the phi-divergence measures. One of them includes the classical likelihood ratio statistic and the other the classical Pearson's statistic for this problem. It is interesting to note that the vector of unknown parameters, in the two new families of phi-divergence statistics considered in this paper, is estimated using the minimum phi-divergence estimator instead of the maximum likelihood estimator. Minimum phi-divergence estimators are a natural extension of the maximum likelihood estimator.

关键词： general linear hypotheses logistic regression model minimum phi-divergence estimator phi-divergence statistic

来源：评论

学校读者我要写书评

暂无评论

Maximum likelihood analysis of logistic regression models with incomplete covariate data and auxiliary information

引用

BIOMETRICS 2001年第1期57卷 34-42页

作者： Horton, NJ Laird, NM Boston Univ Sch Publ Hlth Dept Epidemiol & Biostat Boston MA 02118 USA Boston Univ Sch Med Dept Med Boston MA 02118 USA Harvard Univ Sch Publ Hlth Dept Biostat Boston MA 02115 USA

This article presents a new method for maximum likelihood estimation of logistic regression models with incomplete covariate data where auxiliary information is available. This auxiliary information is extraneous to the regression model of interest but predictive of the covariate with missing data. Ibrahim (1990, Journal of the American Statistical Association 85, 765-769) provides a general method for estimating generalized linear regression models with missing covariates using the EM algorithm that is easily implemented when there is no auxiliary data. Vach (1997, Statistics in Medicine 16, 57-72) describes how the method can be extended when the outcome and auxiliary data are conditionally independent given the covariates in the model. The method allows the incorporation of auxiliary data without making the conditional independence assumption. We suggest tests of conditional independence and compare the performance of several estimators in an example concerning mental health service utilization in children. Using an artificial dataset, we compare the performance of several estimators when auxiliary data are available.

关键词： conditional independence assumption EM algorithm joint maximization logistic regression model missing covariates surrogate information two-stage designs

来源：评论

学校读者我要写书评

暂无评论

Inferences from logistic regression models in the presence of small samples, rare events, nonlinearity, and multicollinearity with observational data

引用

JOURNAL OF APPLIED STATISTICS 2018年第3期45卷 528-546页

作者： Bergtold, Jason S. Yeager, Elizabeth A. Featherstone, Allen M. Kansas State Univ Dept Agr Econ 307 Waters Hall Manhattan KS 66506 USA

The logistic regression model has been widely used in the social and natural sciences and results from studies using this model can have significant policy impacts. Thus, confidence in the reliability of inferences drawn from these models is essential. The robustness of such inferences is dependent on sample size. The purpose of this article is to examine the impact of alternative data sets on the mean estimated bias and efficiency of parameter estimation and inference for the logistic regression model with observational data. A number of simulations are conducted examining the impact of sample size, nonlinear predictors, and multicollinearity on substantive inferences (e.g. odds ratios, marginal effects) when using logistic regression models. Findings suggest that small sample size can negatively affect the quality of parameter estimates and inferences in the presence of rare events, multicollinearity, and nonlinear predictor functions, but marginal effects estimates are relatively more robust to sample size.

关键词： logistic regression model multicollinearity nonlinearity rare events inference small sample bias C18 C35 C83

来源：评论

学校读者我要写书评

暂无评论

Studying noncollapsibility of the odds ratio with marginal structural and logistic regression models

引用

STATISTICAL METHODS IN MEDICAL RESEARCH 2016年第5期25卷 1925-1937页

作者： Pang, Menglan Kaufman, Jay S. Platt, Robert W. McGill Univ Dept Epidemiol Biostat & Occupat Hlth 1020 Pine Ave West Montreal PQ H3A 1A2 Canada

One approach to quantifying the magnitude of confounding in observational studies is to compare estimates with and without adjustment for a covariate, but this strategy is known to be defective for noncollapsible measures such as the odds ratio. Comparing estimates from marginal structural and standard logistic regression models, the total difference between crude and conditional effects can be decomposed into the sum of a noncollapsibility effect and confounding bias. We provide an analytic approach to assess the noncollapsibility effect in a point-exposure study and provide a general formula for expressing the noncollapsibility effect. Next, we provide a graphical approach that illustrates the relationship between the noncollapsibility effect and the baseline risk, and reveals the behavior of the noncollapsibility effect for a range of different exposure and covariate effects. Various observations about noncollapsibility can be made from the different scenarios with or without confounding;for example, the magnitude of effect of the covariate plays a more important role in the noncollapsibility effect than does that of the effect of the exposure. In order to explore the noncollapsibility effect of the odds ratio in the presence of time-varying confounding, we simulated an observational cohort study. The magnitude of noncollapsibility was generally comparable to the effect in the point-exposure study in our simulation settings. Finally, in an applied example we demonstrate that collapsibility can have an important impact on estimation in practice.

关键词： noncollapsibility odds ratio marginal structural model logistic regression model confounding bias

来源：评论

学校读者我要写书评

暂无评论

Examining Individuals' Use of the Internetfor Health Care Activities OverTime: Results from the US National Health Interview Survey

引用

JMIR HUMAN FACTORS 2025年 12卷 e58362页

作者： Junkins, Zachary Zahan, Nusrath Neyens, David Clemson Univ Dept Ind Engn 100 Freeman Hall Clemson SC 29634 USA

Background: Telehealth is an increasingly important component of health care services. Telehealth services may present an opportunity to increase the equity, accessibility, and effectiveness of health care. As such, it is critical that telehealth design focuses on reducing the barriers to access and usability that may impair some telehealth users. Objective: Our goal was to identify different demographic characteristics, behaviors, or opinions that may predict groups who are likely to face a barrier to using telehealth services. Methods: We used data from the National Health Interview Survey and multiple logit regression models focused on different aspects of telehealth to examine threedifferent avenues of telehealth service: looking up health information using the internet, scheduling an appointment using the internet, and communicating with a care provider through email using the internet in order to consider the ways in which different telehealth services may face different barriers. Results: Our results suggest that middle-aged (36-55 years old) and older adult (56-85 years old) respondents were significantly less likely to look up health information using the internet or schedule an appointment using the internet versus younger individuals (18-35 years old). Specifically, our analysis found that middle-aged adults were found to have a higher odds ratio than older adults (0.83 vs 0.65) for looking up health information using the internet. We also found that there were differences in age groups for using technology to perform health care-related tasks. In terms of searching for health information using the internet and scheduling appointments using the internet, wefound differences between men and women, with women being significantly more likely than men to look up health information using the internet, schedule an appointment using the internet, and communicate with a care provider through email using the internet. Across all the investigated variables, we foun

关键词： internet web search internet search internet use searching behavior access to health information telemedicine telehealth virtual care virtual health virtual medicine logistic regression model regression model National Health Interview Survey NHIS

来源：评论

学校读者我要写书评

暂无评论

Stein-type estimation in logistic regression models based on minimum φ-divergence estimators

引用

JOURNAL OF THE KOREAN STATISTICAL SOCIETY 2009年第1期38卷 73-86页

作者： Menendez, M. L. Pardo, L. Pardo, M. C. Univ Complutense Madrid Dept Stat & ORI E-28040 Madrid Spain Tech Univ Madrid ETSAM Dept Appl Math Madrid Spain

In this paper we present a study of Stein-type estimators for the unknown parameters in logistic regression models when it is suspected that the parameters may be restricted to a subspace of the parameter space. The Stein-type estimators studied are based on the minimum phi-divergence estimator instead on the maximum likelihood estimator as well as on phi-divergence test statistics. (C) 2008 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

关键词： logistic regression model Phi-divergence test statistics Minimum phi-divergence estimator General linear hypotheses Stein-type estimation

来源：评论

学校读者我要写书评

暂无评论

Predictors of non-calcified plaques in the coronary arteries of 242 subjects using multislice computed tomography and logistic regression models

引用

INTERNATIONAL JOURNAL OF CARDIOLOGY 2007年第2期117卷 191-197页

作者： Funabashi, Nobusada Asano, Miki Komuro, Issei Chiba Univ Grad Sch Med Dept Cardiovasc Sci & Med Chuo Ku Chiba 2608670 Japan

Objectives: We detected non-calcified plaques (NCPs) in the coronary arteries using multislice computed tomography (MSCT) in order to determine the predictors of NCPs using logistic regression models. Methods: Two hundred and forty-two consecutive subjects (141 males;overall age range, 17-91 years old) underwent enhanced electrocardiogram-gated MSCT to detect NCPs. logistic models for predicting NCPs were developed which incorporated age, sex, coronary calcified-plaque (CP), and the following coronary risk factors (RFs): hypertension (HT), diabetes mellitus (DM), hyperlipidemia (HL), a smoking habit, and obesity. Results: NCPs were detected in 76 subjects (59 males, 35-82 years old [median = 67]) whose average number of coronary RFs was 2.6, 75% of whom presented with HT, 30% with DM, 51% with HL, 64% were present or past cigarette smokers, and 32% were obese. In the 76 subjects with NCPs, the incidence of male sex, presence of HT, a smoking habit, CP and the number of coronary RFs were significantly higher than in the 166 subjects without NCR of the 101 female subjects, 17 showed NCPs and in every case the subject was more than 50 years old. In a logistic regression model, male sex, HT and smoking habit (relative risks 2.7, 2.0, and 2.7 [95% confidence interval = 1.35.6, 1.0-4.0, and 1.5-4.9, respectively]) were associated with increased incidence of NCPs. Conclusions: The incidence of NCPs was significantly increased in the presence of HT and a smoking habit, suggesting that lesions may be caused by HT or smoking-induced vessel injury even in the young male. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

关键词： non-calcified plaques (NCPs) coronary arteries multislice computed tomography (MSCT) predictors logistic regression model

来源：评论

学校读者我要写书评

暂无评论

Diagnostics of multiple group influential observations for logistic regression models

引用

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2019年第16期89卷 3118-3136页

作者： Coskun, Burcin Alpu, O. Univ Eskisehir Osmangazi Inst Educ Sci Eskisehir Turkey Eskisehir Osmangazi Univ Dept Stat TR-26480 Eskisehir Turkey

In this paper, two new multiple influential observation detection methods, *** and mCD*, are introduced for logistic regression. The proposed diagnostic measures are compared with the generalized difference in fits (GDFFITS) and the generalized squared difference in beta (GSDFBETA), which are multiple influential diagnostics. The simulation study is conducted with one, two and five independent variable logistic regression models. The performance of the diagnostic measures is examined for a single contaminated independent variable for each model and in the case where all the independent variables are contaminated with certain contamination rates and intensity. In addition, the performance of the diagnostic measures is compared in terms of the correct identification rate and swamping rate via a frequently referred to data set in the literature.

关键词： Multiple group logistic regression diagnostics suspicious observations influential observations logistic regression model multiple influential observations modified Cook's distance generalized Cook's distance generalized difference in fits generalized standardized Pearson residuals Cook's distance

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：