论文检索

信息性抽样下调查分析的权重构造AI 解读

Sampling related to the outcome variable of a regression analysis conditional on covariates is called informative sampling and may lead to bias in ordinary least squares estimation. Weighting by the reciprocal of the inclusion probability approximately removes such bias but may inflate variance. This paper investigates two ways of modifying such weights to improve efficiency while retaining consistency. One approach is to multiply the inverse probability weights by functions…

聚类无应答下的逆概率加权AI 解读

Correlated nonresponse within clusters arises in certain survey settings. It is often represented by a random effects model and assumed to be cluster-specific nonignorable, in the sense that survey and nonresponse outcomes are conditionally independent given cluster-level random effects. Two basic forms of inverse probability weights are considered: response propensity weights based on a marginal model, and weights based on predicted random effects. It is shown that both…

微观数据的一种披露风险度量AI 解读

Summary Protection against disclosure is important for statistical agencies releasing microdata files from sample surveys. Simple measures of disclosure risk can provide useful evidence to support decisions about release. We propose a new measure of disclosure risk: the probability that a unique match between a microdata record and a population unit is correct. We argue that this measure has at least two advantages. First, we suggest that it may be a more realistic measure…

多层模型中不等选择概率的加权处理AI 解读

Summary When multilevel models are estimated from survey data derived using multistage sampling, unequal selection probabilities at any stage of sampling may induce bias in standard estimators, unless the sources of the unequal probabilities are fully controlled for in the covariates. This paper proposes alternative ways of weighting the estimation of a two-level model by using the reciprocals of the selection probabilities at each stage of sampling. Consistent estimators…

复杂抽样设计下双抽样框调查的估计AI 解读

In a dual frame survey, samples are drawn independently from two overlapping frames that are assumed to cover the population of interest. This article considers the case when at least one of the samples is selected by a complex design involving, e.g., multistage sampling. A “pseudo”—maximum likelihood estimator of a population total or a mean for such dual frame surveys is proposed. An advantage of the proposed estimator is that the same weights are used for all the…

多抽样框调查中迭代比例估计的效率AI 解读

Multiple frame surveys involve the combination of samples selected from separate sampling frames. A topical example is a dual-frame survey that combines a sample of households interviewed by telephone with a sample drawn from a frame including nontelephone households. Various estimators of population totals and means have been proposed for multiple frame surveys. In particular Bankier proposed the application of raking ratio estimation and compared its performance to…

调查抽样中基于模型推断的条件化问题AI 解读

A ‘discontinuity’ of sampling distribution inference between a prediction problem and an estimation problem in model-based survey sampling is discussed. The problem is resolved by conditioning on an appropriate ancillary within a curved exponential family framework. The ignorability of the sampling design for inference is discussed.

调查抽样中基于模型推断的条件化问题AI 解读

A ‘discontinuity’ of sampling distribution inference between a prediction problem and an estimation problem in model-based survey sampling is discussed. The problem is resolved by conditioning on an appropriate ancillary within a curved exponential family framework. The ignorability of the sampling design for inference is discussed.

抽样设计对主成分分析的影响AI 解读

Most sample surveys are multivariate and many lend themselves to multivariate methods of analysis. The most usual mode of such analysis is a standard statistical package, such as BMDP or SPSS, in which the multivariate analyses are based on the underlying assumption that the data are generated as independent observations from a common probability distribution. This assumption ignores the sample selection procedure involved in the survey, which leads to the following basic…

抽样设计对主成分分析的影响AI 解读

Most sample surveys are multivariate and many lend themselves to multivariate methods of analysis. The most usual mode of such analysis is a standard statistical package, such as BMDP or SPSS, in which the multivariate analyses are based on the underlying assumption that the data are generated as independent observations from a common probability distribution. This assumption ignores the sample selection procedure involved in the survey, which leads to the following basic…