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Tests for underlying Markovian structure from panel data with partially aggregated states

部分状态聚合面板数据中潜在马尔可夫结构的检验

SUMMARY For dichotomous longitudinal panel data assumed to have been generated by a Markov chain but with only one of its states identifiable, the likelihood ratio and related tests for underlying Markovian structure are studied. It is shown that the likelihood ratio may be written as a product of conditionally independent likelihood ratios for testing independence in certain contingency tables, given margins. The tests are illustrated on data from malaria and…

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Residual variance and residual pattern in nonlinear regression

非线性回归中的残差方差与残差模式

A nonparametric estimator of residual variance in nonlinear regression is proposed. It is based on local linear fitting. Asymptotically the estimator has a small bias, but a larger variance compared with the parametric estimator in linear regression. Finite sample properties are investigated in a simulation study, including a comparison with other nonparametric estimators. The method is also useful for spotting heteroscedasticity and outliers in the residuals at an early…

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Multilevel mixed linear model analysis using iterative generalized least squares

利用迭代广义最小二乘分析多层混合线性模型

Models for the analysis of hierarchically structured data are discussed. An iterative generalized least squares estimation procedure is given and shown to be equivalent to maximum likelihood in the normal case. There is a discussion of applications to complex surveys, longitudinal data, and estimation in multivariate models with missing responses. An example is given using educational data.

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Longitudinal data analysis using generalized linear models

使用广义线性模型分析纵向数据

This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence. The estimating equations are derived without specifying the joint distribution of a subject's observations yet they reduce to the score equations for niultivariate Gaussian outcomes. Asymptotic theory…

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The Analysis of Panel Data under a Markov Assumption

Markov 假设下面板数据的分析

Methods for the analysis of panel data under a continuous-time Markov model are proposed. We present procedures for obtaining maximum likelihood estimates and associated asymptotic covariance matrices for transition intensity parameters in time homogeneous models, and for other process characteristics such as mean sojourn times and equilibrium distributions. Generalizations to handle covariance analysis and to the fitting of certain nonhomogeneous models are presented, and…

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Multivariate Gamma-Poisson Models

多元伽马—泊松模型

This article extends the multivariate gamma-Poisson model of repeated events, developed by Arbous and Kerrich (1951) and Bates and Neyman (1952), by (a) compounding it with a Dirichlet distribution in the analysis of cross-sectional data and by (b) allowing individual rates to shift at the start of the second period in the analysis of two-period longitudinal data. The first extension allows individuals to specialize in particular types of events. The model is shown to…

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Testing the Error Components Model with Non-Normal Disturbances

非正态扰动下误差成分模型的检验

This paper derives the limit distribution of the test statistics for the error components model proposed by Breusch and Pagan under the assumption of non-normal disturbances and under a sequence of local alternatives, and shows that the Breusch-Pagan tests are robust to non-normal disturbances. The paper also points out that the Breusch-Pagan tests do not make full use of the information provided by the one-sided alternative. And it proposes a one-sided alternative test for…

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A Note on Restricted Maximum Likelihood Estimation with an Alternative Outlier Model

替代异常值模型下限制最大似然估计的一则札记

SUMMARY For single outliers in normal theory fixed effects models a mean slippage model is commonly used. An alternative is to model the outlier as arising from an unknown observation with inflated variance. Maximum likelihood estimates for the position of the outlier under the two models need not agree. This paper considers maximizing a restricted part of the likelihood to estimate the variance parameters and characterizes these estimates in terms of standard least squares…

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Mean Squared Error Properties of Empirical Bayes Estimators in a Multivariate Random Effects General Linear Model

多元随机效应一般线性模型中经验贝叶斯估计量的均方误差性质

Estimation of an individual's regression coefficients is considered in a multivariate general linear model, where it is assumed that the individual's coefficients β k are subject to both fixed effects and random effects over different individuals. The mean squared error matrix of a natural estimator of β k is derived for any individual k, in the general situation where all parameters of the model must be estimated, and is shown to be smaller than the mean squared error…

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Estimating Gross Labor-Force Flows

劳动力状态间总转移流量的估计

We present and apply an adjustment procedure for the Bureau of the Census and Bureau of Labor Statistics gross labor-force flows data that addresses two major defects in the data. First, an adjustment procedure is developed to take account of individuals with missing labor-force classifications who are not missing at random. Second, we provide a procedure for adjustment for individuals with spurious labor-force transitions arising because of classification errors in either…

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How Long Is a Spell of Unemployment? Illusions and Biases in the Use of CPS Data

失业会持续多久?使用 CPS 数据的错觉与偏差

Most data used to study the durations of unemployment spells come from the Current Population Survey, which is a point-in-time survey and gives an incomplete picture of the underlying duration distribution.We introduce a new sample of completed unemployment spells obtained from panel data and apply CPS sampling and reporting techniques to replicate the type of data used by other researchers.Predicted duration distributions derived from this CPS-like data are then compared to…

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The analysis of binary longitudinal data with time independent covariates

具有时间不变协变量的二元纵向数据分析

This paper considers extensions of logistic regression to the case where the binary outcome variable is observed repeatedly for each subject. We propose two working models that lead to consistent estimates of the regression parameters and of their variances under mild assumptions about the time dependence within each subject's data. The efficiency of the proposed estimators is examined. An analysis of stress in mothers with infants is presented to illustrate the proposed…

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Two-Sample Asymptotically Distribution-Free Tests for Incomplete Multivariate Observations

不完整多元观测的两样本渐近分布无关检验

Asymptotically distribution-free tests for equality of two multivariate distributions based on censored observations are proposed. By choosing appropriate test scores, we obtain the multivariate versions of the Gehan and log-rank tests. An important application of the proposed tests is in the area in which multiple observations are collected on study subjects, some of whom may have missing observations. The patterns of missing observations are allowed to differ for the two…

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Econometric Models for Count Data with an Application to the Patents-R & D Relationship

计数数据的计量模型:专利与研发关系的应用

This paper focuses on developing and adapting statistical models of counts (nonnegative integers) in the context of panel data and using them to analyze the relationship between patents and R & D expenditures. Since a variety of other economic data come in the form of repeated counts of some individual actions or events, the methodology should have wide applications. The statistical models we develop are applications and generalizations of the Poisson distribution. Two…

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Testing for Neglected Heterogeneity

被忽略异质性的检验

Develops a specification error test sensitive to negelected heterogeneity, which is viewed as causing parameter variation, by deriving a score test of the hypothesis that parameters have zero variance. The test turns out to be the Information Matrix test and is a useful diagnostic for researchers using cross-sectional or longitudinal data to estimate models of individual economic agents behavior. -from Author specification error neglected heterogeneity parameter variation…

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Pseudo Maximum Likelihood Methods: Applications to Poisson Models

伪极大似然方法:泊松模型的应用

Pseudo maximum likelihood techniques are applied to basic Poisson models and to Poisson models with specification errors. In the latter case it is shown that consistent and asymptotically normal estimators can be obtained without specifying the p.d.f. of the disturbances. These estimators are compared both from the finite sample and the asymptotic point of view. Quasi generalized PML estimators, which asymptotically dominate all PML estimators, are also proposed. Finally,…

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Estimation and Hypothesis Testing for Collections of Autoregressive Time Series

多条自回归时间序列的估计与假设检验

The analysis of a number of independent first-order autoregressive time series is considered in a normal theory context. A model is studied which allows for nonstation-ary and nonidentical distribution of the series caused by both fixed effect and random effect components.

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Nonparametric Regression Analysis of Growth Curves

生长曲线的非参数回归分析

In recent years, nonparametric curve estimates have been extensively explored in theoretical work. There has, however, been a certain lack of convincing applications, in particular involving comparisons with parametric techniques. The present investigation deals with the analysis of human height growth, where longitudinal measurements were collected for a sample of boys and a sample of girls. Evidence is presented that kernel estimates of acceleration and velocity of height,…

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Nonlinear Regression with Dependent Observations

相依观测下的非线性回归

This paper provides general conditions which ensure consistency and asymptotic normality for the nonlinear least squares estimator. These conditions apply to time-series, cross-section, panel, or experimental data for single equations as well as systems of equations. The regression errors may be serially correlated and/or heteroscedastic. For an important special case, we propose a new covariance matrix estimator which is consistent regardless of the presence of…

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Estimation and hypothesis testing for collections of autoregressive time series

多组自回归时间序列的估计与假设检验

The analysis of a number of independent first-order autoregressive time series is considered in a normal theory context. A model is studied which allows for nonstation-ary and nonidentical distribution of the series caused by both fixed effect and random effect components.

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