Performance Characteristics of Profiling Methods and the Impact of Inadequate Case-mix Adjustment [0.03%]
配置文件方法的性能特征以及病例组合调整不足的影响
Yanjun Chen,Damla Şentürk,Jason P Estes et al.
Yanjun Chen et al.
Profiling or evaluation of health care providers involves the application of statistical models to compare each provider's performance with respect to a patient outcome, such as unplanned 30-day hospital readmission, adjusted for patient ca...
MAXIMUM LIKELIHOOD ESTIMATION OF GAUSSIAN COPULA MODELS FOR GEOSTATISTICAL COUNT DATA [0.03%]
地理统计计数数据的高斯copula模型的最大似然估计
Zifei Han,Victor De Oliveira
Zifei Han
This work investigates the computation of maximum likelihood estimators in Gaussian copula models for geostatistical count data. This is a computationally challenging task because the likelihood function is only expressible as a high dimens...
BiMM tree: A decision tree method for modeling clustered and longitudinal binary outcomes [0.03%]
用于建模聚类和纵向二元结果的决策树方法-BiMM树
Jaime Lynn Speiser,Bethany J Wolf,Dongjun Chung et al.
Jaime Lynn Speiser et al.
Clustered binary outcomes are frequently encountered in clinical research (e.g. longitudinal studies). Generalized linear mixed models (GLMMs) for clustered endpoints have challenges for some scenarios (e.g. data with multi-way interactions...
An R package for model fitting, model selection and the simulation for longitudinal data with dropout missingness [0.03%]
一个用于具有脱落缺失的纵向数据分析建模、模型选择和模拟的R软件包
Cong Xu,Zheng Li,Yuan Xue et al.
Cong Xu et al.
Missing data arise frequently in clinical and epidemiological fields, in particular in longitudinal studies. This paper describes the core features of an R package wgeesel, which implements marginal model fitting (i.e., weighted generalized...
Monte Carlo studies of bootstrap variability in ROC analysis with data dependency [0.03%]
数据相关性对ROC分析中Bootstrap变化性影响的蒙特卡洛研究
Jin Chu Wu,Alvin F Martin,Raghu N Kacker
Jin Chu Wu
ROC analysis involving two large datasets is an important method for analyzing statistics of interest for decision making of a classifier in many disciplines. And data dependency due to multiple use of the same subjects exists ubiquitously ...
A study of the properties of Gaussian mixture model for stable isotope standard quantification in MALDI-TOF MS [0.03%]
高斯混合模型在基质辅助激光解析电离飞行时间质谱稳定同位素标准定量中的性质研究
John Christian G Spainhour,Michael G Janech,Viswanathan Ramakrishnan
John Christian G Spainhour
The quantification of peptides in Matrix assisted laser desorption/ionization time-of-flight mass spectrum analysis coupled with stable isotope standards has been used to quantify native peptides under many experimental conditions. This app...
Nezamoddin N Kachouie,Xihong Lin,Armin Schwartzman
Nezamoddin N Kachouie
Feature extraction from observed noisy samples is a common important problem in statistics and engineering. This paper presents a novel general statistical approach to the region detection problem in long data sequences. The proposed techni...
Nonparametric Bootstrap of Sample Means of Positive-Definite Matrices with an Application to Diffusion-Tensor-Imaging Data Analysis [0.03%]
扩散张量成像数据中正定矩阵样本均值的非参数自助法
Leif Ellingson,David Groisser,Daniel Osborne et al.
Leif Ellingson et al.
This paper presents nonparametric two-sample bootstrap tests formeans of randomsymmetric positivedefinite (SPD) matrices according to two differentmetrics: the Frobenius (or Euclidean)metric, inherited from the embedding of the set of SPD m...
Optimal inference for Simon's two-stage design with over or under enrollment at the second stage [0.03%]
Simon两阶段设计中第二阶段超量或减量抽样时的最优推断方法
Guogen Shan,John J Chen
Guogen Shan
Simon's two-stage designs are widely used in clinical trials to assess the activity of a new treatment. In practice, it is often the case that the second stage sample size is different from the planned one. For this reason, the critical val...
An efficient Bayesian approach for Gaussian Bayesian network structure learning [0.03%]
一种高效的高斯贝叶斯网络结构学习的贝叶斯方法
Shengtong Han,Hongmei Zhang,Ramin Homayouni et al.
Shengtong Han et al.
This article proposes a Bayesian computing algorithm to infer Gaussian directed acyclic graphs (DAG's). It has the ability of escaping local modes and maintaining adequate computing speed compared to existing methods. Simulations demonstrat...