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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Non-response is a source of error in surveys that appears when part of the data to be collected are not observed. It has the potential to bias significantly the results of the survey and, consequently, to prevent valid inference.Non-response reduces the sample size, and therefore increases the variance of estimators, leading to larger margins of error.A more serious effect of non-response is that it can be selective. This occurs if, due to non-response, specific groups are under- or over-represented in the survey. To say it in other word: estimates are significantly too high or too low.There are statistical procedures to overcome non-response bias using auxiliary information.In this book, some estimators have been proposed for the estimation of population mean using auxiliary information under non-response. The relative efficiencies of proposed estimators are illustrated with two real populations.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Non-response is a source of error in surveys that appears when part of the data to be collected are not observed. It has the potential to bias significantly the results of the survey and, consequently, to prevent valid inference.Non-response reduces the sample size, and therefore increases the variance of estimators, leading to larger margins of error.A more serious effect of non-response is that it can be selective. This occurs if, due to non-response, specific groups are under- or over-represented in the survey. To say it in other word: estimates are significantly too high or too low.There are statistical procedures to overcome non-response bias using auxiliary information.In this book, some estimators have been proposed for the estimation of population mean using auxiliary information under non-response. The relative efficiencies of proposed estimators are illustrated with two real populations.