Methods for Stratified Cluster Sampling with Informative Stratification
نویسندگان
چکیده
منابع مشابه
Methods for Stratified Cluster Sampling with Informative Stratification
We look at fitting regression models using data from stratified cluster samples when the strata may depend in some way on the observed responses within clusters. One important subclass of examples is that of family studies in genetic epidemiology, where the probability of selecting a family into the study depends on the incidence of disease within the family. We develop the survey-weighted esti...
متن کاملResearch Article Methods for Stratified Cluster Sampling with Informative Stratification
We look at fitting regression models using data from stratified cluster samples when the strata may depend in some way on the observed responses within clusters. One important subclass of examples is that of family studies in genetic epidemiology, where the probability of selecting a family into the study depends on the incidence of disease within the family. We develop the survey-weighted esti...
متن کاملEdgeworth expansions for two-stage sampling with applications to stratified and cluster sampling
A two-term Edgeworth expansion for the standardized version of the sample total in a two-stage sampling design is derived. In particular, for the commonly used stratified and cluster sampling schemes, formal two-term asymptotic expansions are obtained for the Studentized versions of the sample total. These results are applied in conjunction with the bootstrap to construct more accurate confiden...
متن کاملAdaptive optimal allocation in stratified sampling methods
In this paper, we propose a stratified sampling algorithm in which the random drawings made in the strata to compute the expectation of interest are also used to adaptively modify the proportion of further drawings in each stratum. These proportions converge to the optimal allocation in terms of variance reduction. And our stratified estimator is asymptotically normal with asymptotic variance e...
متن کاملFunctional quantization-based stratified sampling methods
In this article, we propose several quantization based stratified sampling methods to reduce the variance of a Monte-Carlo simulation. Theoretical aspects of stratification lead to a strong link between the problem of optimal Lquantization of a random variable and the variance reduction that can be achieved. We first emphasize on the consistency of quantization for designing strata in stratifie...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Applied Mathematics and Decision Sciences
سال: 2007
ISSN: 1173-9126,1532-7612
DOI: 10.1155/2007/56372