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Analysing longitudinal count data with overdispersion

过度离散纵向计数数据的分析

In many biomedical studies, longitudinal count data comprise repeated responses and a set of multidimensional covariates for a large number of individuals. When the response variable in such models is subject to overdispersion, the overdispersion parameter influences the marginal variance. In such cases, the overdispersion parameter plays a significant role in efficient estimation of the regression parameters. This raises the need for joint estimation of the regression…

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Multiple-Output Production With Undesirable Outputs

含非期望产出的多产出生产模型

Many production processes yield both good outputs and undesirable ones (e.g., pollutants). In this article we develop a generalization of a stochastic frontier model that is appropriate for such technologies. We discuss efficiency analysis and, in particular, define technical and environmental efficiency in the context of our model. We develop methods for carrying out Bayesian inference and apply them to a panel data set of Dutch dairy farms, where excess nitrogen production…

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Marginal Longitudinal Nonparametric Regression

纵向边际模型中的非参数回归

We consider nonparametric regression in a longitudinal marginal model of generalized estimating equation (GEE) type with a time-varying covariate in the situation where the number of observations per subject is finite and the number of subjects is large. In such models, the basic shape of the regression function is affected only by the covariate values and not otherwise by the ordering of the observations. Two methods of estimating the nonparametric function can be…

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The Effect of Duration and Delay of Licensure on Risk of Crash

持照时长与延迟取证对交通事故风险的影响

The driving history records of a sample of 13,794 Michigan public school students were followed for up to 13 years from their initial time-of-license to determine the separate effects of duration of licensure and delay of licensure on risk of crash. We propose a subject-specific lognormal accelerated failure time to model the expected time-to-crash as a function of age at time of licensure, duration of licensure, and a set of control covariates. When multiple time-to-crash…

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Unit root tests in panel data: asymptotic and finite-sample properties

面板数据单位根检验:渐近与有限样本性质

We consider pooling cross-section time series data for testing the unit root hypothesis. The degree of persistence in individual regression error, the intercept and trend coefficient are allowed to vary freely across individuals. As both the cross-section and time series dimensions of the panel grow large, the pooled t-statistic has a limiting normal distribution that depends on the regression specification but is free from nuisance parameters. Monte Carlo simulations…

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An Empirical Analysis of Earnings and Employment Risk

收入与就业风险的实证分析

The mean and higher moments of the distribution of future income are crucial determinants of individual choices. These moments are usually estimated in panel data from past income realizations. In this article we rely instead on subjective expectations available in the 1995 Survey of Household Income and Wealth, a large random sample representative of Italian households. The survey elicits information on the distribution of future earnings and on the probability of…

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A semiparametric pseudolikelihood estimation method for panel count data

面板计数数据的半参数伪似然估计方法

In this paper, we study panel count data with covariates. A semiparametric pseudolikelihood estimation method is proposed based on the assumption that, given a covariate vector Z, the underlying counting process is a nonhomogeneous Poisson process with the conditional mean function given by E{N (t) |Z} = Λ0 (t) exp (β′0Z). The proposed estimation method is shown to be robust in the sense that the estimator converges to its true value regardless of whether or not N (t) is a…

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Varying-coefficient models and basis function approximations for the analysis of repeated measurements

重复测量分析中的变系数模型与基函数近似

A global smoothing procedure is developed using basis function approximations for estimating the parameters of a varying‐coefficient model with repeated measurements. Inference procedures based on a resampling subject bootstrap are proposed to construct confidence regions and to perform hypothesis testing. Conditional biases and variances of our estimators and their asymptotic consistency are developed explicitly. Finite sample properties of our procedures are investigated…

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Estimating and interpolating a Markov chain from aggregate data

利用聚合数据估计与插值马尔可夫链

Given aggregated longitudinal data generated by a Markov chain, which may be nonhomogeneous, the problem considered is that of modelling, estimating and interpolating the logarithms of partial odds and hence the transition probabilities. By partial odds is meant the probability of a transition to another state divided by the probability of no transition. A result establishing asymptotic normality leads to vector weighted least squares estimation of parameterised partial odds…

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Analysis of Multivariate Longitudinal Outcomes With Nonignorable Dropouts and Missing Covariates

含不可忽略退出和缺失协变量的多元纵向结果分析

This article analyzes changes in treatment practices in outpatient methadone treatment units from a national panel study. The analysis of this dataset is challenging due to several difficulties, including multiple longitudinal outcomes, nonignorable nonresponses, and missing covariates. Specifically, the data included several variables that measure the effectiveness of methadone treatment practices for each unit. A substantial percentage of units (33%%) did not respond…

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Determining the Number of Factors in Approximate Factor Models

确定近似因子模型中的因子数

In this paper we develop some econometric theory for factor models of large dimensions. The focus is the determination of the number of factors (r), which is an unresolved issue in the rapidly growing literature on multifactor models. We first establish the convergence rate for the factor estimates that will allow for consistent estimation of r. We then propose some panel criteria and show that the number of factors can be consistently estimated using the criteria. The…

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A segment‐level hazard approach to studying household purchase timing decisions

家庭购买时点决策的分群风险率方法

Abstract The increasing availability of customer‐level data and the willingness of marketers to customize the timing of their offers to consumers makes the accurate segment‐level description of household purchase timing decisions a compelling issue. In this paper we employ a finite mixture accelerated failure time model to identify and characterize household segments in terms of their purchasing rates and their propensity to accelerate purchases due to marketing mix…

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Causal Inference for Complex Longitudinal Data: The Continuous Case

We extend Robins’ theory of causal inference for complex longitudinal data to the case of continuously varying as opposed to discrete covariates and treatments. In particular we establish versions of the key results of the discrete theory: the $g$-computation formula and a collection of powerful characterizations of the $g$-null hypothesis of no treatment effect. This is accomplished under natural continuity hypotheses concerning the conditional distributions of the outcome…

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Semiparametric Nonlinear Mixed-Effects Models and Their Applications

半参数非线性混合效应模型及其应用

Nonlinear mixed effects models (NLMMs) and self-modeling nonlinear regression (SEMOR) models are often used to fit repeated measures data. They use a common function shared by all subjects to model variation within each subject and some fixed and/or random parameters to model variation between subjects. The parametric NLMM may be too restrictive, and the semiparametric SEMOR model ignores correlations within each subject. In this article we propose a class of semiparametric…

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Moment Estimation With Attrition

存在样本流失时的矩估计

We study the effects of the attrition of firms from longitudinal samples on the estimates of dynamic labor demand models. The reasons for attrition from business-based longitudinal samples are extremely varied and are related to both the economic activity of the business and the methods of acquiring sampling frame information for those businesses. We do an exhaustive study of the available information regarding the attrition of French firms from our analysis sample. We…

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Optimal Permutation Tests for the Analysis of Group Randomized Trials

群组随机试验分析的最优置换检验

Two facts complicate the comparison of interventions in group randomized trials (GRT's), a family of clinical trials in which each member of a particular group receives the same treatment assignment. First, individual outcomes within each group are often correlated. Second, the number of groups in a GRT is often not sufficient to make asymptotic approximations possible. Therefore, the tests used with methods, such as generalized estimating equations (GEE) and penalized quasi…

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A Bayesian Model for Detecting Acute Change in Nonlinear Profiles

检测非线性个体曲线急剧变化的贝叶斯模型

We propose a model for longitudinal data with random effects that includes model-based smoothing of measurements over time. This research is motivated by experiments evaluating the hemodynamic effects of various agents in tumor-bearing rats. In one set of experiments, the rats breathed room air, followed by carbogen (a mixture of pure oxygen and carbon dioxide). The experimental responses are longitudinal measurements of oxygen pressure measured in tissue, tumor blood flow,…

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Purchasing Power Parity Tests in Cointegrated Panels

This paper employs recently developed techniques for testing hypotheses in cointegrated panels to test the strong version of purchasing power parity for a panel of post Bretton Woods data. We compare results using fully modified and dynamic OLS approaches, and strongly reject the hypothesis. We also introduce a new between-dimension dynamic OLS estimator and find that the between-dimension FMOLS and DOLS estimates of the long-run deviation from purchasing power parity are…

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