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1,428
Monitoring the future: National survey results on drug use
 I: Secondary school students (NIH Publication No. 055726). Bethesda, MD: National Institute on Drug Abuse
, 2005
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Poststratification Into Many Categories Using Hierarchical Logistic Regression
, 1997
"... A standard method for correcting for unequal sampling probabilities and nonresponse in sample surveys is poststratification: that is, dividing the population into several categories, estimating the distribution of responses in each category, and then counting each category in proportion to its size ..."
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Cited by 34 (13 self)
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in the population. We consider poststratification as a general framework that includes many weighting schemes used in survey analysis (see Little, 1993). We construct a hierarchical logistic regression model for the mean of a binary response variable conditional on poststratification cells. The hierarchical model
Poststratification and Weighting Adjustments
 In
, 2000
"... Introduction 1.1 Overview Poststratification and weighting are used to adjust for known or expected discrepancies between sample and population. In this chapter, we aim to review current methods for using these techniques in survey analysis, and to critically examine the methods in the context of ..."
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Cited by 15 (3 self)
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Introduction 1.1 Overview Poststratification and weighting are used to adjust for known or expected discrepancies between sample and population. In this chapter, we aim to review current methods for using these techniques in survey analysis, and to critically examine the methods in the context
Poststratification and conditional variance estimation
 Journal of the American Statistical Association
, 1993
"... Poststratification estimation is a technique used in sample surveys to improve efficiency of estimators. Survey weights are adjusted to force the estimated numbers of units in each of a set of estimation cells to be equal to known population totals. The resulting weights are then used in forming es ..."
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Cited by 12 (6 self)
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Poststratification estimation is a technique used in sample surveys to improve efficiency of estimators. Survey weights are adjusted to force the estimated numbers of units in each of a set of estimation cells to be equal to known population totals. The resulting weights are then used in forming
Bayesian multilevel estimation with poststratification: Statelevel estimates from national polls
 Political Analysis
, 2004
"... We fit a multilevel logistic regression model for the mean of a binary response variable conditional on poststratification cells. This approach combines the modeling approach often used in smallarea estimation with the population information used in poststratification (see Gelman and Little 1997, S ..."
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Cited by 38 (5 self)
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We fit a multilevel logistic regression model for the mean of a binary response variable conditional on poststratification cells. This approach combines the modeling approach often used in smallarea estimation with the population information used in poststratification (see Gelman and Little 1997
NONPARAMETRIC ENDOGENOUS POSTSTRATIFICATION ESTIMATION
"... Abstract: Poststratification is used to improve the precision of survey estimators when categorical auxiliary information is available from external sources. In natural resource surveys, such information may be obtained from remote sensing data classified into categories and displayed as maps. Thes ..."
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Abstract: Poststratification is used to improve the precision of survey estimators when categorical auxiliary information is available from external sources. In natural resource surveys, such information may be obtained from remote sensing data classified into categories and displayed as maps
A Simulation Study of Cell Collapsing in Poststratification
"... A standard procedure in poststratification is to collapse or combine cells when the sample sizes fall below some minimum or the weight adjustments are above some maximum. Collapsing may decrease the variance of an estimate but may simultaneously increase its bias. We study the effects on bias and va ..."
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A standard procedure in poststratification is to collapse or combine cells when the sample sizes fall below some minimum or the weight adjustments are above some maximum. Collapsing may decrease the variance of an estimate but may simultaneously increase its bias. We study the effects on bias
Sampling Variances for Surveys With Weighting, Poststratification, and Raking
, 2000
"... It is common practice to use weighting, poststratification, and raking to correct for sampling and nonsampling biases and to improve efficiency of estimation in sample surveys. However, there is no standard method for computing sampling variances of estimates that use these adjustments in combinatio ..."
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Cited by 2 (1 self)
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It is common practice to use weighting, poststratification, and raking to correct for sampling and nonsampling biases and to improve efficiency of estimation in sample surveys. However, there is no standard method for computing sampling variances of estimates that use these adjustments
An Examination Of Poststratification Techniques For The Behavioral Risk Factor
"... Randomdigitdialing surveys such as the Behavioral Risk Factor Surveillance System (BRFSS) typically poststratify on age by gender by race/ethnicity cells using control totals from an appropriate source such as the 2000 Census, the Current Population Survey, or the American Community Survey. Using ..."
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Randomdigitdialing surveys such as the Behavioral Risk Factor Surveillance System (BRFSS) typically poststratify on age by gender by race/ethnicity cells using control totals from an appropriate source such as the 2000 Census, the Current Population Survey, or the American Community Survey. Using
Recursive Restriction Estimation: An Alternative to PostStratification in Surveys
"... Numerous government surveys of natural resources use PostStratifi cation to improve statistical effi ciency, where strata are defi ned by fullcoverage, remotely sensed data and geopolitical boundaries. Recursive Restriction Estimation, which may be considered a special case of the static Kalman fi ..."
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Numerous government surveys of natural resources use PostStratifi cation to improve statistical effi ciency, where strata are defi ned by fullcoverage, remotely sensed data and geopolitical boundaries. Recursive Restriction Estimation, which may be considered a special case of the static Kalman fi lter, is an attractive alternative. It decomposes a complex estimation problem into simple components that are sequentially processed. Compared to PostStratifi cation, it more effi ciently uses remotely sensed data, both continuous and categorical. It is less constrained by sample size, which is especially important with panel surveys. It produces a conditionally unbiased covariance matrix for the vector estimate of population totals without approximations or ad hoc assumptions. This facilitates variance estimates for nonlinear pseudoestimators. A robust sequential algorithm controls numerical errors inherent with Recursive Restriction Estimator, which can otherwise cause unreliable results. Analysis of residuals can detect other anomalies.
Results 1  10
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1,428