By Ray Chambers, Robert Clark
This article brings jointly very important principles at the model-based method of pattern survey, which has been constructed during the last 20 years. appropriate for graduate scholars statisticians, it strikes from easy rules basic to sampling to extra rigorous mathematical modelling and information research and comprises routines and strategies.
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Extra info for An Introduction to Model-Based Survey Sampling with Applications
8) to give the sample size required for the target RSE of the present survey. To illustrate this situation, consider the case where in a past survey of the same population (or one very much like it), with sample size m, say, an estimated RSE equal to B was obtained. 9) by Cˆ = B 2 /1002 . 8) above, and discarding lower order terms leads to n = (B 2 /A2 )m. That is, the ratio of the estimated relative standard errors from both surveys is the inverse of the ratio of the square roots of the respective sample sizes for the surveys.
8 Deﬁning Stratum Boundaries So far we have not addressed the important issues of how many strata there should be, or exactly how these strata should be deﬁned. Sample frames often contain one or more auxiliary variables whose values can be used to form strata. For example, a business survey frame will typically contain variables that characterise the industrial classiﬁcation of each business on the frame as well as variables that measure the size of each business in terms of number of employees or amount of tax paid.
1), the sample mean of Y within each of the strata is an EB predictor of the corresponding stratum population mean. The predictor tˆEB of the overall population total ty y is then the sum of the individual stratum level expansion estimators tˆE yh , since these are EB predictors of the stratum population totals tyh of Y , that is tˆEB = tˆSy = y h tˆE yh = h Nh y¯sh . 2) Here h indexes the strata, Nh is the stratum population size, nh is the stratum sample size and y¯sh is the sample mean of Y in stratum h.