Multiple frame sampling theory and applications

Download
2010
Dalçık, Aylin
One of the most important practical problems in conducting sample surveys is the list that can be used for selecting the sample is generally incomplete or out of date. Therefore, sample surveys can produce seriously biased estimates of the population parameters. On the other hand updating a list is a difficult and very expensive operation. Multiple-frame sampling refers to surveys where two or more frames are used and independent samples are taken respectively from each of the frames. It is assumed that the union of the different frames covers the whole population. There are two major reasons for the use of multiple-frame sampling method. One is that, using two or more frames can cover most of the target population and therefore reduces biases due to coverage error. The second is that multipleframe sampling design may result in considerable cost savings over a single frame design.

Suggestions

Robust estimation and hypothesis testing under short-tailedness and inliers
Akkaya, Ayşen (Springer Science and Business Media LLC, 2005-06-01)
Estimation and hypothesis testing based on normal samples censored in the middle are developed and shown to be remarkably efficient and robust to symmetric short-tailed distributions and to inliers in a sample. This negates the perception that sample mean and variance are the best robust estimators in such situations (Tiku, 1980; Dunnett, 1982).
Univariate Sample Size Determination by Alternative Components: Issues on Design Efficiency for Complex Samples
Yozgatlıgil, Ceylan (Exeley, Inc., 2018-06-01)
Sample size determination for any sample survey can be based on the desired objectives of the survey as well as the level of confidence of the desired estimates for some survey variables, the desired precision of the survey results and the size of the population. In addition to these, the cost of enumeration can also be considered as an important criterion for sample size determination. Recently, some international organizations have been using univariate sample size determination approaches for their multi...
A computational approach to nonparametric regression: bootstrapping cmars method
Yazıcı, Ceyda; Batmaz, İnci; Department of Statistics (2011)
Bootstrapping is a resampling technique which treats the original data set as a population and draws samples from it with replacement. This technique is widely used, especially, in mathematically intractable problems. In this study, it is used to obtain the empirical distributions of the parameters to determine whether they are statistically significant or not in a special case of nonparametric regression, Conic Multivariate Adaptive Regression Splines (CMARS). Here, the CMARS method, which uses conic quadr...
Robust control charts
Çetinyürek, Aysun; Sürücü, Barış; Department of Statistics (2006)
Control charts are one of the most commonly used tools in statistical process control. A prominent feature of the statistical process control is the Shewhart control chart that depends on the assumption of normality. However, violations of underlying normality assumption are common in practice. For this reason, control charts for symmetric distributions for both long- and short-tailed distributions are constructed by using least squares estimators and the robust estimators -modified maximum likelihood, trim...
Sample design and allocation for random digit dialling
Ayhan, HO; İslam, Muhammed Qamarul (Springer Science and Business Media LLC, 2005-10-01)
Sample design and sample allocation methods are developed for random digit dialling in household telephone surveys. The proposed method is based on a two-way stratification of telephone numbers. A weighted probability proportional to size sample allocation technique is used, with auxiliary variables about the telephone coverage rates, within local telephone exchanges of each substrata. This makes the sampling design nearly "self-weighting" in residential numbers when the prior information is well assigned. ...
Citation Formats
A. Dalçık, “Multiple frame sampling theory and applications,” M.S. - Master of Science, Middle East Technical University, 2010.