Mean Cost and Cost-Effectiveness Ratios with Censored Data: a Tutorial and SAS® Macros [0.03%]
删失数据下的平均成本及成本效果比：教程和SAS宏代码
Eduard Poltavskiy,Dingning Liu,Shuai Chen et al.
Eduard Poltavskiy et al.
Censoring is an unignorable issue when analyzing survival data and/or medical cost data. Medical costs may be viewed as a type of survival data-in that they accrue over time until an endpoint such as death-or a 'mark' variable. Since Lin et...
Finite Markov chains with absorbing states and mis-specified random effects: application to cognitive data [0.03%]
具有吸收状态的有限马尔可夫链和误指定的随机效应：认知数据的应用
Pei Wang,Changrui Liu,Jiyeon Park et al.
Pei Wang et al.
Finite Markov chains with absorbing states are valuable tools for analyzing longitudinal data with categorical responses. However, defining the one-step transition probabilities in terms of fixed and random effects presents challenges due t...
Adjusting for bias due to measurement error in functional quantile regression models with error-prone functional and scalar covariates [0.03%]
带有误差的函数和标量协变量的功能分位数回归模型中测量误差引起的偏差校正
Xiwei Chen,Heyang Ji,Yuanyuan Luan et al.
Xiwei Chen et al.
Wearable devices enable the continuous monitoring of physical activity (PA) but generate complex functional data with poorly characterized errors. Most work on functional data views the data as smooth, latent curves obtained at discrete tim...
Analysis of Familial Aggregation Using Recurrence Risk for Complex Survey Data [0.03%]
利用复杂调查数据的再发风险分析家族聚集性
Cong Wang,Zhaohai Li,Barry I Graubard
Cong Wang
Familial or family aggregation of a disease is important for studying possible genetic etiology of a disease. A popular and useful measure of family aggregation is recurrence risk. Household health surveys with (family) network sampling, wh...
Global Odds Model with Proportional Odds and Trend Odds Applied to Gross and Microscopic Brain Infarcts [0.03%]
应用于脑梗死的全局比例优势模型与趋势优势模型
Ana W Capuano,Robert Wilson,Julie A Schneider et al.
Ana W Capuano et al.
Medical and epidemiological researchers commonly study ordinal measures of symptoms or pathology. Some of these studies involve two correlated ordinal measures. There is often an interest in including both measures in the modeling. It is co...
Relationship between Obuchowski-Rockette-Hillis and Gallas methods for analyzing multi-reader diagnostic imaging data with empirical AUC as the reader performance measure [0.03%]
基于经验AUC的多阅片人诊断影像数据的Obuchowski-Rockette-Hillis与Gallas方法之间的关系分析
Stephen L Hillis
Stephen L Hillis
For analyzing multireader multicase (MRMC) diagnostic imaging data when the reader performance measure of interest is the area under the receiver-operating-characteristic curve (AUC), two popular methods of analysis that allow conclusions t...
Nonparametric inference of complier quantile treatment effects in randomized trials with imperfect compliance [0.03%]
随机对照试验中依从性不佳下的编序者分位数治疗效应的非参数推断
Lu Mao
Lu Mao
To analyze randomized trials with imperfect compliance, a standard approach is to estimate the local average treatment effect in the sub-population of compliers using randomization status as an instrumental variable. Though quantile analysi...
Norberto Pantoja-Galicia,Olivia I Okereke,Deborah Blacker et al.
Norberto Pantoja-Galicia et al.
The receiver operating characteristic (ROC) curve displays sensitivity versus 1-specificity over a set of thresholds. The area under the ROC curve (AUC) is a global scalar summary of this curve. In the context of time-dependent ROC methods,...
Estimating the AUC with a Graphical Lasso Method for High-dimensional Biomarkers with LOD [0.03%]
基于图论Lasso方法的高维检测限数据AUC估计
Jirui Wang,Yunpeng Zhao,Liansheng Larry Tang
Jirui Wang
This manuscript estimates the area under the receiver operating characteristic curve (AUC) of combined biomarkers in a high-dimensional setting. We propose a penalization approach to the inference of precision matrices in the presence of th...
A Statistical Review: Why Average Weighted Accuracy, not Accuracy or AUC? [0.03%]
统计评估方法综述：为什么是平均加权准确率而非准确率或AUC？
Yunyun Jiang,Qing Pan,Ying Liu et al.
Yunyun Jiang et al.
Sensitivity and specificity are key aspects in evaluating the performance of diagnostic tests. Accuracy and AUC are commonly used composite measures that incorporate sensitivity and specificity. Average Weighted Accuracy (AWA) is motivated ...