Efficient estimation for the multivariate Cox model with missing covariates [0.03%]
具有缺失协变量的多元Cox模型的有效估计方法研究
Youngjoo Cho,Soyoung Kim,Kwang Woo Ahn
Youngjoo Cho
Missing covariates are a ubiquitous issue in the data analysis. One of the widely-used approaches for efficient parameter estimation is using augmentation based on the semiparametric efficiency theory. However, existing methods for right-ce...
Estimating random effects in a finite Markov chain with absorbing states: Application to cognitive data [0.03%]
具有吸收状态的有限马尔可夫链中随机效应的估计：认知数据的应用
Pei Wang,Erin L Abner,Changrui Liu et al.
Pei Wang et al.
Finite Markov chains with absorbing states are popular tools for analyzing longitudinal data with categorical responses. The one step transition probabilities can be defined in terms of fixed and random effects but it is difficult to estima...
A phenomenological model for COVID-19 data taking into account neighboring-provinces effect and random noise [0.03%]
考虑相邻省份影响和随机噪声的COVID-19数据现象学模型
Julia Calatayud,Marc Jornet,Jorge Mateu
Julia Calatayud
We model the incidence of the COVID-19 disease during the first wave of the epidemic in Castilla-Leon (Spain). Within-province dynamics may be governed by a generalized logistic map, but this lacks of spatial structure. To couple the provin...
Sally Hunsberger,Lori Long,Sarah E Reese et al.
Sally Hunsberger et al.
This paper develops methods to test for associations between two variables with clustered data using a U-Statistic approach with a second-order approximation to the variance of the parameter estimate for the test statistic. The tests that a...
Change-point analysis through integer-valued autoregressive process with application to some COVID-19 data [0.03%]
基于整数自回归过程的结构突变分析及其在新冠疫情数据中的应用
Subhankar Chattopadhyay,Raju Maiti,Samarjit Das et al.
Subhankar Chattopadhyay et al.
In this article, we consider the problem of change-point analysis for the count time series data through an integer-valued autoregressive process of order 1 (INAR(1)) with time-varying covariates. These types of features we observe in many ...
Mixed-effects models for health care longitudinal data with an informative visiting process: A Monte Carlo simulation study [0.03%]
具有信息性访问过程的医疗保健纵向数据混合效应模型的蒙特卡洛模拟研究
Alessandro Gasparini,Keith R Abrams,Jessica K Barrett et al.
Alessandro Gasparini et al.
Electronic health records are being increasingly used in medical research to answer more relevant and detailed clinical questions; however, they pose new and significant methodological challenges. For instance, observation times are likely ...
Maarten Marsman,Lourens Waldorp,Fabian Dablander et al.
Maarten Marsman et al.
We propose to use the squared multiple correlation coefficient as an effect size measure for experimental analysis-of-variance designs and to use Bayesian methods to estimate its posterior distribution. We provide the expressions for the sq...
Itai Dattner,Shota Gugushvili
Itai Dattner
In this paper, we study application of Le Cam's one-step method to parameter estimation in ordinary differential equation models. This computationally simple technique can serve as an alternative to numerical evaluation of the popular non-l...
Alexander Ly,Maarten Marsman,Eric-Jan Wagenmakers
Alexander Ly
Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian s...
Non-parametric regression in clustered multistate current status data with informative cluster size [0.03%]
具有信息量群大小的聚类多重状态当前状况数据中的非参数回归
Ling Lan,Dipankar Bandyopadhyay,Somnath Datta
Ling Lan
Datasets examining periodontal disease records current (disease) status information of tooth-sites, whose stochastic behavior can be attributed to a multistate system with state occupation determined at a single inspection time. In addition...