• Corpus ID: 88511760

Dealing with nonresponse in survey sampling: a latent modeling approach

@article{Matei2012DealingWN,
  title={Dealing with nonresponse in survey sampling: a latent modeling approach},
  author={Alina Matei and Maria Giovanna Ranalli},
  journal={arXiv: Methodology},
  year={2012}
}
Nonresponse is present in almost all surveys and can severely bias estimates. It is usually distinguished between unit and item nonresponse: in the former, we completely fail to have information from a unit selected in the sample, while in the latter, we observe only part of the information on the selected unit. Unit nonresponse is usually dealt with by reweighting: each unit selected in the sample has associated a sampling weight and an unknown response probability; the initial sampling weight… 

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References

SHOWING 1-10 OF 52 REFERENCES
A method of weighting adjustment for survey data subject to nonignorable nonresponse
Weighting adjustment is a standard quasi-randomization approach for survey data subject to nonresponse (Little, 1986). The existing methods are typically based on the assumption that nonresponse is
Estimation With Survey Data Under Nonignorable Nonresponse or Informative Sampling
Nonresponse is a very common phenomenon in survey sampling. Nonignorable nonresponse—that is, a response mechanism that depends on the values of the variable having nonresponse—is the most difficult
Nonresponse weighting adjustment using estimated response probability
To reduce nonresponse bias in sample surveys, a method of nonresponse weighting adjustment is often used which consists of multiplying the sampling weight of the respondent by the inverse of the
Experiments in Producing Nonresponse Bias
While nonresponse rates in household surveys are increasing in most industrialized nations, the increasing rates do not always produce nonresponse bias in survey estimates. The linkage between
Nonresponse Rates and Nonresponse Bias in Household Surveys
Many surveys of the U.S. household population are experiencing higher refusal rates. Nonresponse can, but need not, induce nonresponse bias in survey estimates. Recent empirical findings illustrate
3. A Partial Independence Item Response Model for Surveys with Filter Questions
In many surveys, responses to earlier questions determine whether later questions are asked. The probability of an affirmative response to a given item is therefore nonzero only if the participant
Weighting for item non‐response in attitude scales by using latent variable models with covariates
We discuss the use of latent variable models with observed covariates for computing response propensities for sample respondents. A response propensity score is often used to weight item and unit
Survey estimation under informative nonresponse with follow-up
TLDR
Two different approaches that make use of the follow-up data are presented, the first based on weighting and the other on prediction, with appropriate variance estimators developed for each case.
The problem of non-response in sample surveys.
TLDR
A technique which combines the advantages of both procedures is indicated, and under reasonable assumptions as to the relative costs of the two methods of canvass, an allocation of the sample can be made to mail and field canvasses.
Empirical Bayes and Item-Clustering Effects in a Latent Variable Hierarchical Model
TLDR
This work simultaneously estimates all parameters of an expanded model that considers item clustering and ignoring uncertainty about model parameters on an important outcome measure that NAEP report, causing substantial underestimation of standard errors and induces a modest bias in location estimates.
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