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Survey Weights: A Step-by-step Guide to Calculation

Autor Richard Valliant, Jill A. Dever
en Limba Engleză Paperback – 8 ian 2018
Survey Weights: A Step-by-Step Guide to Calculation is the first guide geared toward Stata users that systematically covers the major steps taken in creating survey weights. These weights are used to project a sample to some larger population and can be computed for either probability or nonprobability samples. Sample designs can range from simple, single-stage samples to more complex, multistage samples, each of which may use specialized steps in weighting to account for selection probabilities, nonresponse, inaccurate coverage of a population by a sample, and auxiliary data to improve precision and compensate for coverage errors. The authors provide many examples with Stata code.
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Specificații

ISBN-13: 9781597182607
ISBN-10: 1597182605
Pagini: 184
Dimensiuni: 188 x 245 x 18 mm
Greutate: 0.41 kg
Ediția:1
Editura: Stata Press
Colecția Stata Press

Public țintă

Academic, Postgraduate, and Professional Practice & Development

Cuprins

Overview of weighting. Initial steps in weighting probability samples. Adjustments for nonresponse. Calibration and other uses of auxiliary data in weighting. Use of weights in variance estimation. Nonprobability samples. Weighting for some special cases. Quality of survey weights.

Notă biografică

Richard Valliant, PhD, is a research professor emeritus at the Institute for Social Research of the University of Michigan and at the Joint Program in Survey Methodology at the
University of Maryland.
Jill A. Dever, PhD, is a senior research statistician/director at RTI International in
Washington, D.C. and assistant research professor at the Joint Program in Survey
Methodology at the University of Maryland.

Descriere

Survey Weights: A Step-by-Step Guide to Calculation is the first guide geared towards Stata users that systematically covers the major steps taken in creating survey weights. These weights are used to project a sample to some larger population and can be computed for either probability or nonprobability samples.