The Effects of a Mid‐Data Collection Change in Financial Incentives on Total Survey Error in the National Survey of Family Growth

Wagner, James; West, Brady T.; Guyer, Heidi; Burton, Paul F.; Kelley, Jason; Couper, Mick P.; Mosher, William D.

doi:10.1002/9781119041702.ch8

Cited by 7 publications

(3 citation statements)

References 29 publications

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“…In the second stage, the interviewer seeks a 60- to 80-minute “main” interview from the selected person using CAPI; the response rate to this main interview is 70 percent on average. This relatively high response rate is enabled by the use of RSD strategies (Wagner et al 2012), “tokens of appreciation” for respondent participation that can be as high as US$80 (Wagner et al 2017), and general completion of the “main” interview by the same interviewer who conducted the screening interview.…”

Section: Methodsmentioning

confidence: 99%

Sources of Variance in the Accuracy of Interviewer Observations

West

Li²

2017

Sociological Methods & Research

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In face-to-face surveys, interviewer observations are a cost-effective source of paradata for nonresponse adjustment of survey estimates and responsive survey designs. Unfortunately, recent studies have suggested that the accuracy of these observations can vary substantially among interviewers, even after controlling for household-, area-, and interviewer-level characteristics, limiting their utility. No study has identified sources of this unexplained variance in observation accuracy. Motivated by theoretical expectations from the observer bias literature, this study analyzed more than 45,000 open-ended justifications provided by interviewers in the U.S. National Survey of Family Growth (NSFG) for their observations on two key features of all sampled NSFG households: presence of children and expected probability of household response. The study finds that variability among interviewers in the cues used to record these observations (evident from the open-ended justifications) explains much of the previously unexplained variance in observation accuracy.

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Section: Methodsmentioning

confidence: 99%

Sources of Variance in the Accuracy of Interviewer Observations

West

Li²

2017

Sociological Methods & Research

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“…NSFG paradata are aggregated on a daily basis and used to predict the probability that active households will respond to either the screening interview or the main interview. Survey managers might use these predictions for prioritization of active cases (e.g., Wagner et al, 2012 ) or for stratifying the sample when selecting a subsample of active cases for the new data collection protocol after 10 weeks ( Wagner et al, 2017 ). At this point, managers may oversample high-propensity cases, or offer a higher token of appreciation to encourage response.…”

Section: Methodsmentioning

confidence: 99%

What Do You Think? Using Expert Opinion to Improve Predictions of Response Propensity Under a Bayesian Framework

Coffey

West

Wagner

et al. 2020

Methods

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“…In this case, that seems reasonable as the coefficients represent estimated changes in hours when characteristics of the sample are changed. This method has been used previously to estimate costs in surveys (Wagner et al 2017).…”

Section: Alternative Modeling Approachesmentioning

confidence: 99%

Comparing the Ability of Regression Modeling and Bayesian Additive Regression Trees to Predict Costs in a Responsive Survey Design Context

Wagner

West

Elliott

et al. 2020

Journal of Official Statistics

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Responsive survey designs rely upon incoming data from the field data collection to optimize cost and quality tradeoffs. In order to make these decisions in real-time, survey managers rely upon monitoring tools that generate proxy indicators for cost and quality. There is a developing literature on proxy indicators for the risk of nonresponse bias. However, there is very little research on proxy indicators for costs and almost none aimed at predicting costs under alternative design strategies. Predictions of survey costs and proxy error indicators can be used to optimize survey designs in real time. Using data from the National Survey of Family Growth, we evaluate alternative modeling strategies aimed at predicting survey costs (specifically, interviewer hours). The models include multilevel regression (with random interviewer effects) and Bayesian Additive Regression Trees (BART).

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The Effects of a Mid‐Data Collection Change in Financial Incentives on Total Survey Error in the National Survey of Family Growth

Cited by 7 publications

References 29 publications

Sources of Variance in the Accuracy of Interviewer Observations

Sources of Variance in the Accuracy of Interviewer Observations

What Do You Think? Using Expert Opinion to Improve Predictions of Response Propensity Under a Bayesian Framework

Comparing the Ability of Regression Modeling and Bayesian Additive Regression Trees to Predict Costs in a Responsive Survey Design Context

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