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信息性临床就诊下电子健康记录的重复事件分析AI 解读

Although increasingly used as a data resource for assembling cohorts, electronic health records (EHRs) pose many analytic challenges. In particular, a patient's health status influences when and what data are recorded, generating sampling bias in the collected data. In this paper, we consider recurrent event analysis using EHR data. Conventional regression methods for event risk analysis usually require the values of covariates to be observed throughout the follow-up period.…

用条件方法与协变量分解区分组间和组内效应AI 解读

Summary We consider the situation where the random effects in a generalized linear mixed model may be correlated with one of the predictors, which leads to inconsistent estimators. We show that conditional maximum likelihood can eliminate this bias. Conditional likelihood leads naturally to the partitioning of the covariate into between- and within-cluster components and models that include separate terms for these components also eliminate the source of the bias. Another…

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广义线性混合模型的最大似然算法AI 解读

Maximum likelihood algorithms are described for generalized linear mixed models. I show how to construct a Monte Carlo version of the EM algorithm, propose a Monte Carlo Newton-Raphson algorithm, and evaluate and improve the use of importance sampling ideas. Calculation of the maximum likelihood estimates is feasible for a wide variety of problems where they were not previously. I also use the Newton-Raphson algorithm as a framework to compare maximum likelihood to the…

一类二项响应混合模型中后验分布存在性的说明AI 解读

Necessary and sufficient conditions are given for the existence of the posterior distribution of the variance components in a class of mixed models for binomial responses. The implications of our results are illustrated through an example.

一类二项响应混合模型后验分布存在性的说明AI 解读

Necessary and sufficient conditions are given for the existence of the posterior distribution of the variance components in a class of mixed models for binomial responses. The implications of our results are illustrated through an example.

二元数据方差分量的极大似然估计AI 解读

We consider a class of probit-normal models for binary data and describe ML and REML estimation of variance components for that class as well as best prediction for the realized values of the random effects. ML estimates are calculated using an EM algorithm; for complicated models EM includes a Gibbs step. The computations are illustrated through two examples.

用于检测受约束自由回忆中聚集现象的多项游程检验AI 解读

Psychologists often want to detect category structure in subjects' free recall protocols. Although runs tests based on the binomial distribution are commonly used to detect nonrandomness within a sequence, many research situations require tests based on the multinomial distribution. We propose a test of randomness versus clustering based on the number of runs in multinomial data. We illustrate its use with data from a mass communication experiment using a constrained free…

检测受限自由回忆中聚集现象的多项游程检验AI 解读

Psychologists often want to detect category structure in subjects' free recall protocols. Although runs tests based on the binomial distribution are commonly used to detect nonrandomness within a sequence, many research situations require tests based on the multinomial distribution. We propose a test of randomness versus clustering based on the number of runs in multinomial data. We illustrate its use with data from a mass communication experiment using a constrained free…

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正确选择概率的 Olkin-Sobel-Tong 估计量的小样本性质AI 解读

In the problem of selecting the best of k populations, Olkin, Sobel, and Tong (1976) have introduced the important idea of a posteriori analysis of the data (as opposed to the usual formulation), in which design of the experiment is the major consideration. They considered the large-sample properties of an estimator that has been discussed further by Gibbons, Olkin, and Sobel (1977), Gupta and Panchapakesan (1979), and Tong (1980). In this article we study the small-sample…

对称矩阵求导及其应用AI 解读

Dwyer (1967) provided extensive formulas for matrix derivatives, many of which are for derivatives with respect to symmetric matrices. The results of his article are only for symmetric matrices whose (j, i) element is considered to differ from the (i, j) element even though their scalar values are equal. A simple result is given that extends the use of Dwyer's formulas to symmetric matrices in which the (i, j) element is considered functionally equal to the (j, i) element.…

对称矩阵求导及其应用AI 解读

Dwyer (1967) provided extensive formulas for matrix derivatives, many of which are for derivatives with respect to symmetric matrices. The results of his article are only for symmetric matrices whose (j, i) element is considered to differ from the (i, j) element even though their scalar values are equal. A simple result is given that extends the use of Dwyer's formulas to symmetric matrices in which the (i, j) element is considered functionally equal to the (j, i) element.…