SEQUENTIAL DATA WEIGHTING PROCEDURES FOR COMBINED RATIO ESTIMATORS IN COMPLEX SAMPLE SURVEYS

In sample surveys weighting is applied to data to increase the quality of estimates. Data weighting can be used for several purposes. Sample design weights can be used to adjust the differences in selection probabilities for non-self weighting sample designs. Sample design weights, adjusted for nonresponse and non-coverage through the sequential data weighting process. The unequal selection probability designs represented the complex sampling designs. Among many reasons of weighting, the most important reasons are weighting for unequal probability of selection, compensation for nonresponse, and post-stratification. Many highly efficient estimation methods in survey sampling require strong information about auxiliary variables, x. The most common estimation methods using auxiliary information in estimation stage are regression and ratio estimator. This paper proposes a sequential data weighting procedure for the estimators of combined ratio mean in complex sample surveys and general variance estimation for the population ratio mean. To illustrate the utility of the proposed estimator, Turkish Demographic and Health Survey 2003 real life data is used. It is shown that the use of auxiliary information on weights can considerably improve the efficiency of the estimates

Sequential data weighting procedures for combined ratio estimators ın complex sample surveys

In sample surveys weighting is applied to data to increase the quality of estimates. Data weighting can be used for several purposes. Sample design weights can be used to adjust the differences in selection probabilities for non-self weighting sample designs. Sample design weights, adjusted for nonresponse and noncoverage through the sequential data weighting process. The unequal selection probability designs represented the complex sampling designs. Among many reasons of weighting, the most important reasons are weighting for unequal probability of selection, compensation for nonresponse, and post-stratification. Many highly efficient estimation methods in survey sampling require strong information about auxiliary variables, x. The most common estimation methods using auxiliary information in estimation stage are regression and ratio estimator. This paper proposes a sequential data weighting procedure for the estimators of combined ratio mean in complex sample surveys and general variance estimation for the population ratio mean. To illustrate the utility of the proposed estimator, Turkish Demographic and Health Survey 2003 real life data is used. It is shown that the use of auxiliary information on weights can considerably improve the efficiency of the estimates

Computer-assisted joint space area measurement: a new technique in patients with knee osteoarthritis

WOS: 000418648300010PubMed: 29901022Objectives: This study aims to assess the validity and reproducibility of computer-assisted joint space area measurement in knee roentgenograms of patients with knee osteoarthritis and compare it with a qualitative method in knee roentgenograms and quantitative and semi-quantitative methods in magnetic resonance imaging. Patients and methods: The study included 40 knees of 40 patients diagnosed as osteoarthritis (14 males, 26 females; mean age 57.4 +/- 5.9 years; range 47 to 67 years). Only the patients who wrote consents for publication of their radiologic data, and with knee roentgenograms and magnetic resonance images of the same knees were selected. Computer-assisted measurements were applied to joint spaces by two blinded physicians, for two times with an interval of one week. Data were evaluated for intraobserver and interobserver consistency. Also, data were compared with qualitative (Kellgren-Lawrence classification), quantitative (joint space width, cartilage thickness, meniscal thickness in magnetic resonance images) and semi-quantitative methods (whole-organ magnetic resonance imaging score). Results: Intraobserver consistency was evaluated for each physician, which revealed no differences. Interobserver consistency was evaluated by comparing the measurements of two blinded physicians and no differences were found (p>0.05). There was no significant correlation between the grade of Kellgren-Lawrence classification and other variables; such as grade of meniscus, meniscal thickness, cartilage thickness and computer-assisted joint space area measurements (p>0.05). While there was a positive correlation between computer-assisted joint space area measurement and other quantitative measurements, there was a negative correlation between computer-assisted joint space area measurement and whole-organ magnetic resonance imaging scores. Conclusion: When compared with qualitative, quantitative, and semi-quantitative methods, computer-assisted joint space area measurement seems to be a useful, reproducible, and cost-effective quantitative method for evaluating knee osteoarthritis