Practical Tools for Designing and Weighting Survey Samples

Valliant, Richard; Dever, Jill A.; Kreuter, Frauke

doi:10.1007/978-1-4614-6449-5

Cited by 175 publications

(136 citation statements)

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“…The statistical price paid for bias reduction using w sel and w nr is increased standard errors for weighted estimates. In contrast, poststratification weighting (w ps ) to external population controls can lead to reduced standard errors of sample estimates or may attenuate sampling biases due to sample frame noncoverage [20].…”

Section: Complex Sample Designs and Design Effectsmentioning

confidence: 98%

Attributable fraction estimation from complex sample survey data

Heeringa

Berglund

West

et al. 2015

Annals of Epidemiology

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Section: Complex Sample Designs and Design Effectsmentioning

confidence: 98%

Attributable fraction estimation from complex sample survey data

Heeringa

Berglund

West

et al. 2015

Annals of Epidemiology

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“…For this design, just the strata identifiers, PSU identifiers and weights provide sufficient design information for constructing consistent variance estimators. Valliant, Dever and Kreuter (2013), Chapter 15, describe how this may be done for linear estimators such as the HT estimator. For more complex nonlinear estimators, the method of linearization (more commonly referred to as the delta method in mainstream statistics) may be employed.…”

Section: Variance Estimationmentioning

confidence: 99%

Introduction to the Design and Analysis of Complex Survey Data

Skinner¹,

Wakefield²

2017

Statist. Sci.

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Abstract. We give a brief overview of common sampling designs used in a survey setting, and introduce the principal inferential paradigms under which data from complex surveys may be analyzed. In particular, we distinguish between design-based, model-based and model-assisted approaches. Simple examples highlight the key differences between the approaches. We discuss the interplay between inferential approaches and targets of inference and the important issue of variance estimation.

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“…Undercoverage can lead to bias if the propensity to be included in the sampling frame is related to a survey variable of interest (Valliant, Dever, & Frauke, 2003). For example, if field staff tend to omit low-income households, which are less likely to have Internet access, then estimates of household Internet access may be biased due to frame errors.…”

Section: Coverage Error In Housing Unit Listingsmentioning

confidence: 99%

Assessing Accuracy and Coverage of Housing Units Sampling Frame using the Post-Frame Update Survey (PFS) Method

Elawad¹,

Nardis²,

Agied³

2017

AJHSS

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Survey research using nationally representative samples is growing substantially in the rapidly developing countries of the Gulf Cooperation Council (GCC). However, in such countries the population and their demographic makeup change at some of the fastest rates in the world. In Qatar for instance, government censuses tend to be undertaken every five to six years, while the population and its demographic composition change very quickly (Alrouh, Ismail & Cheema, 2013). In 2004, the population of Qatar was just 798,000 and Qataris represented 24% of the countryâ€™s residents. The 2010 census measured the population at 1,699,000, only 17% of which were Qataris.In such countries therefore, sampling frames based on censuses may quickly become outdated as demographic compositions change considerably over short time periods, more so than in other countries. These contexts present a challenge for survey research, as the target population may differ significantly from the sampling frame shortly after it is constructed. Outdated frames may lead to coverage and content errors that not only affect the estimates produced by a survey but also operational processes associated with data collection. Frame error can negatively impact time spent in the field and survey costs. Periodic evaluation of the quality of a sampling frame used between censuses is required for estimating coverage bias and informing researchers about the quality of the frame data. Adjustments in field operations can then be made to improve the effectiveness and efficiency of data collection.This paper describes the Post-Frame update Survey method conducted by the Social and Economic Survey Research Institute (SESRI) at Qatar University. It aims to assess the accuracy and coverage of its housing units sampling frame and improve field operations. This method of evaluating sampling frames could be applicable to other research organizations that survey rapidly changing populations.Â

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Practical Tools for Designing and Weighting Survey Samples

Cited by 175 publications

References 0 publications

Attributable fraction estimation from complex sample survey data

Attributable fraction estimation from complex sample survey data

Introduction to the Design and Analysis of Complex Survey Data

Assessing Accuracy and Coverage of Housing Units Sampling Frame using the Post-Frame Update Survey (PFS) Method

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