Analysis

All (2) ((2 results))

• 1. Conditional and unconditional analysis of some small area estimators in complex sampling Archived

  Articles and reports: 12-001-X20030016608

  Description:

  This work deals with the unconditional and conditional properties of some well-known small area estimators: expansion, post-stratified ratio, synthetic, composite, sample size dependent and the empirical best linear unbiased predictor (EBLUP). A two-stage sampling design is considered as it is commonly used in household surveys conducted by the National Statistics Institute of Italy. An evaluation is carried out through a simulation based on 1991 Italian census data. The small areas considered are the local labour market areas, which are unplanned domains that cut across the boundaries of the design strata.

  Release date: 2003-07-31

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• 2. Empirical comparison of small area estimation methods for the Italian Labour Force Survey Archived

  Articles and reports: 12-001-X199400214419

  Description:

  The study was undertaken to evaluate some alternative small areas estimators to produce level estimates for unplanned domains from the Italian Labour Force Sample Survey. In our study, the small areas are the Health Service Areas, which are unplanned sub-regional territorial domains and were not isolated at the time of sample design and thus cut across boundaries of the design strata. We consider the following estimators: post-stratified ratio, synthetic, composite expressed as linear combination of synthetic and of post-stratified ratio, and sample size dependent. For all the estimators considered in this study, the average percent relative biases and the average relative mean square errors were obtained in a Monte Carlo study in which the sample design was simulated using data from the 1981 Italian Census.

  Release date: 1994-12-15

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Articles and reports (2) ((2 results))

• 1. Conditional and unconditional analysis of some small area estimators in complex sampling Archived

  Articles and reports: 12-001-X20030016608

  Description:

  This work deals with the unconditional and conditional properties of some well-known small area estimators: expansion, post-stratified ratio, synthetic, composite, sample size dependent and the empirical best linear unbiased predictor (EBLUP). A two-stage sampling design is considered as it is commonly used in household surveys conducted by the National Statistics Institute of Italy. An evaluation is carried out through a simulation based on 1991 Italian census data. The small areas considered are the local labour market areas, which are unplanned domains that cut across the boundaries of the design strata.

  Release date: 2003-07-31

  ---

• 2. Empirical comparison of small area estimation methods for the Italian Labour Force Survey Archived

  Articles and reports: 12-001-X199400214419

  Description:

  The study was undertaken to evaluate some alternative small areas estimators to produce level estimates for unplanned domains from the Italian Labour Force Sample Survey. In our study, the small areas are the Health Service Areas, which are unplanned sub-regional territorial domains and were not isolated at the time of sample design and thus cut across boundaries of the design strata. We consider the following estimators: post-stratified ratio, synthetic, composite expressed as linear combination of synthetic and of post-stratified ratio, and sample size dependent. For all the estimators considered in this study, the average percent relative biases and the average relative mean square errors were obtained in a Monte Carlo study in which the sample design was simulated using data from the 1981 Italian Census.

  Release date: 1994-12-15

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