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边界处密度函数的改进估计量AI 解读

We propose a new method of boundary correction for kernel density estimation. The technique is a kind of generalized reflection method involving reflecting a transformation of the data. The transformation depends on a pilot estimate of the logarithmic derivative of the density at the boundary. In simulations, the new method is seen to clearly outperform an earlier generalized reflection idea. It also has overall advantages over boundary kernel methods and a nonnegative…

基于经验特征函数的时间序列假设检验：广义谱密度方法AI 解读

The standardized spectral density completely describes serial dependence of a Gaussian process. For non-Gaussian processes, however, it may become an inappropriate analytic tool, because it misses the nonlinear processes with zero autocorrelation. By generalizing the concept of the standardized spectral density, I propose a new spectral tool suitable for both linear and nonlinear time series analysis. The generalized spectral density is indexed by frequency and a pair of…

二元响应回归中的降维AI 解读

The idea of dimension reduction without loss of information can be quite helpful for guiding the construction of summary plots in regression without requiring a prespecified model. Focusing on the central subspace, we investigate such “sufficient” dimension reduction in regressions with a binary response. Three existing methods—sliced inverse regression, principal Hessian direction, and sliced average variance estimation—and one new method—difference of covariances—are…

二元响应数据的一类新偏斜链接模型AI 解读

The logit, probit, and student t-links are widely used in modeling dichotomous quantal response data. Most of the commonly used link functions are symmetric, except the complementary log-log link. However, in some applications the overall fit can be significantly improved by the use of an asymmetric link. In this article we propose a new skewed link model for analyzing binary response data with covariates. Introducing a skewed distribution for the underlying latent variable,…

具有类似最大似然性质的缺失协变量加权估计方程AI 解读

In regression analysis, missing covariate data occurs often. A recent approach to analyzing such data is weighted estimating equations. With weighted estimating equations, the contribution to the estimating equation from a complete observation is weighted by the inverse probability of being observed. In this article we propose a weighted estimating equation that is almost identical to the maximum likelihood estimating equations. As such, we propose an EM-type algorithm to…

利用半参数无应答模型调整不可忽略的随访退出AI 解读

Consider a study whose design calls for the study subjects to be followed from enrollment (time t = 0) to time t = T, at which point a primary endpoint of interest Y is to be measured. The design of the study also calls for measurements on a vector V t) of covariates to be made at one or more times t during the interval [0, T). We are interested in making inferences about the marginal mean μ0 of Y when some subjects drop out of the study at random times Q prior to the common…

零售客户层面的贸易促销建模：约束参数层级模型的应用AI 解读

We consider the problem of utilizing data at the retail/market level on sales and marketing mix variables to help manufacturers optimize the allocation of trade promotional budgets across areas. Major consumer packaged goods manufacturers budget at least one-half of their total marketing expenses to trade promotions. Trade promotional deals are designed to encourage retailers to promote products by temporarily reducing the price, putting them in in-store displays, or…

非实验研究中的因果效应：重新评估培训项目评价AI 解读

This article uses propensity score methods to estimate the treatment impact of the National Supported Work (NSW) Demonstration, a labor training program, on postintervention earnings. We use data from Lalonde's evaluation of nonexperimental methods that combine the treated units from a randomized evaluation of the NSW with nonexperimental comparison units drawn from survey datasets. We apply propensity score methods to this composite dataset and demonstrate that, relative to…

用广义断点回归设计评估加利福尼亚州囚犯分类系统AI 解读

Published studies using the regression discontinuity design have been limited to cases in which linear regression is applied to a categorical treatment indicator and an equal interval outcome. This is unnecessarily narrow. We show here how a generalization the usual regression discontinuity design can be applied in a wider range of situations. We focus on the use of categorical treatment and response variables, but we also consider the more general case of any regression…

名义分组间部分测量潜在特质的比较AI 解读

This article presents a method for estimating the subgroup distributions of a latent trait measured as a normal variate in the population. This problem occurs in large-scale assessments, such as the National Assessment of Educational Progress, the National Adult Literacy Survey, and other programs where proficiencies are estimated via marginal maximum likelihood through a model based on item-response theory. Heretofore, estimates of subgroup means were often estimated using…

非可忽略缺失的分类生活质量数据矩估计程序AI 解读

Quality-of-life outcomes collected during clinical trials often have considerable amounts of missing data, which, if not appropriately accounted for, may lead to bias in inferences. We introduce a method-of-moments (MM) estimating procedure for a model designed to handle nonignorable missingness arising in categorical data measured on independent populations. The missingness mechanism is assumed to be the same across the populations. We derive necessary and sufficient…

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心理学中的零假设检验争论AI 解读

A controversy concerning the usefulness of “null” hypothesis tests in scientific inference has continued in articles within psychology since 1960 and has recently come to a head, with serious proposals offered for a test ban or something close to it. This article sketches some of the views of statistical theory and practice among different groups of psychologists, reviews a recent book offering multiple perspectives on null hypothesis tests, and argues that the debate within…

基于秩的自回归阶数识别AI 解读

Optimal rank-based procedures have been derived for testing arbitrary linear restrictions on the parameters of autoregressive moving average (ARMA) models with unspecified innovation densities. The finite-sample performances of these procedures are investigated here in the context of AR order identification and compared to those of classical (partial correlograms and Lagrange multipliers) methods. The results achieved by rank-based methods are quite comparable, in the…

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非线性或非正态回归：基于似然分析的简便精确p值AI 解读

We develop simple approximations for the p values to use with regression models having linear or nonlinear parameter structure and normal or nonnormal error distribution; computer iteration then gives confidence intervals. Both frequentist and Bayesian versions are given. The approximations are derived from recent developments in likelihood analysis and have third-order accuracy. Also, for very small and medium-sized samples, the accuracy can typically be high. The…

复发事件时间数据的条件回归分析AI 解读

Recurrence time data can be regarded as a specific type of correlated survival data in which recurrent event times of a subject are stochastically ordered. Given the ordinal nature of recurrence times, this article focuses on conditional regression analysis. A semiparametric hazards model, including the structural and episode-specific parameters, is proposed for recurrence time data. In this model the order of episodes serves as the stratification variable. Estimation of the…

具有类似最大似然性质的缺失协变量加权估计方程AI 解读

In regression analysis, missing covariate data occurs often. A recent approach to analyzing such data is weighted estimating equations. With weighted estimating equations, the contribution to the estimating equation from a complete observation is weighted by the inverse probability of being observed. In this article we propose a weighted estimating equation that is almost identical to the maximum likelihood estimating equations. As such, we propose an EM-type algorithm to…

美国各州失业率的层级贝叶斯估计AI 解读

Under a federal-state cooperative program, the U.S. Bureau of Labor Statistics (BLS) publishes monthly unemployment rate estimates for its 50 states and the District of Columbia. The primary source of data for this estimation problem is the Current Population Survey (CPS). However, the CPS state unemployment rate estimates are unreliable, because the survey provides relatively few observations per state. Various federal agencies use state-level unemployment rate estimates…

不可忽略缺失下分类生活质量数据的矩估计AI 解读

Quality-of-life outcomes collected during clinical trials often have considerable amounts of missing data, which, if not appropriately accounted for, may lead to bias in inferences. We introduce a method-of-moments (MM) estimating procedure for a model designed to handle nonignorable missingness arising in categorical data measured on independent populations. The missingness mechanism is assumed to be the same across the populations. We derive necessary and sufficient…