Donald Hedeker,Robin J Mermelstein,Hakan Demirtas et al.
Donald Hedeker et al.
In health studies, questionnaire items are often scored on an ordinal scale, for example on a Likert scale. For such questionnaires, item response theory (IRT) models provide a useful approach for obtaining summary scores for subjects (i.e....
Evaluating and Comparing Methods for Measuring Spatial Access to Mammography Centers in Appalachia (Re-Revised) [0.03%]
评估和比较阿巴拉契亚地区乳腺癌筛查中心空间可达性测量方法
Joseph Donohoe,Vincent Marshall,Xi Tan et al.
Joseph Donohoe et al.
Purpose: This study evaluated spatial access to mammography centers in Appalachia using both traditional access measures and the two-step floating catchment area (2SFCA) method. ...
Estimating causal effects: considering three alternatives to difference-in-differences estimation [0.03%]
因果效应的估计：三种差分法估计的替代方法之比较
Stephen O&#x;Neill,Noémi Kreif,Richard Grieve et al.
Stephen O&#x;Neill et al.
Difference-in-differences (DiD) estimators provide unbiased treatment effect estimates when, in the absence of treatment, the average outcomes for the treated and control groups would have followed parallel trends over time. This assumption...
Peter Congdon
Peter Congdon
Analysis of healthy life expectancy is typically based on a binary distinction between health and ill-health. By contrast, this paper considers spatial modelling of disease free life expectancy taking account of the number of chronic condit...
Mike Baiocchi,Dylan S Small,Lin Yang et al.
Mike Baiocchi et al.
Classic instrumental variable techniques involve the use of structural equation modeling or other forms of parameterized modeling. In this paper we use a nonparametric, matching-based instrumental variable methodology that is based on a stu...
A comparison of alternative strategies for choosing control populations in observational studies [0.03%]
观察性研究中选择控制人群的替代策略比较
Adam Steventon,Richard Grieve,Jasjeet S Sekhon
Adam Steventon
Various approaches have been used to select control groups in observational studies: (1) from within the intervention area; (2) from a convenience sample, or randomly chosen areas; (3) from areas matched on area-level characteristics; and (...
A Monte Carlo method to estimate the confidence intervals for the concentration index using aggregated population register data [0.03%]
利用聚合人口登记数据估计浓度指数的置信区间的蒙特卡洛方法
Sonja Lumme,Reijo Sund,Alastair H Leyland et al.
Sonja Lumme et al.
In this paper, we introduce several statistical methods to evaluate the uncertainty in the concentration index (C) for measuring socioeconomic equality in health and health care using aggregated total population register data. The C is a wi...
A Bivariate Mixed-Effects Location-Scale Model with application to Ecological Momentary Assessment (EMA) data [0.03%]
具有应用到生态 moment assessment 数据的二元混合效应位置尺度模型
Oksana Pugach,Donald Hedeker,Robin Mermelstein
Oksana Pugach
A bivariate mixed-effects location-scale model is proposed for estimation of means, variances, and covariances of two continuous outcomes measured concurrently in time and repeatedly over subjects. Modeling the two outcomes jointly allows e...
ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME [0.03%]
估计潜在类别对远处结果的影响时解决混杂问题的方法
Megan S Schuler,Jeannie-Marie S Leoutsakos,Elizabeth A Stuart
Megan S Schuler
Confounding is widely recognized in settings where all variables are fully observed, yet recognition of and statistical methods to address confounding in the context of latent class regression are slowly emerging. In this study we focus on ...
Using propensity scores in difference-in-differences models to estimate the effects of a policy change [0.03%]
利用倾向值评估政策变化的影响：差分差异模型中的倾向值法
Elizabeth A Stuart,Haiden A Huskamp,Kenneth Duckworth et al.
Elizabeth A Stuart et al.
Difference-in-difference (DD) methods are a common strategy for evaluating the effects of policies or programs that are instituted at a particular point in time, such as the implementation of a new law. The DD method compares changes over t...