The Effect of Nonresponse and Measurement Error on Wage Regression across Survey Modes

Kirchner, Antje; Felderer, Barbara

doi:10.1002/9781119041702.ch24

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…Experimental studies comparing the response rates of web surveys with those of other survey modes have reported higher response rates for traditional survey modes (Fricker, Galesic, Tourangeau, and Yan 2005;Kirchner and Felderer 2016). By contrast, a substantial body of literature has emphasized the advantages of web surveys over traditional modes (Greene, Speizer, and Wiitala 2008;Boyle, Morrison, MacDonald, Duncan, and Rose 2016).…”

Section: Introductionmentioning

confidence: 99%

Web Versus Other Survey Modes: An Updated and Extended Meta-Analysis Comparing Response Rates

Daikeler

Bošnjak

Manfreda

2019

Journal of Survey Statistics and Methodology

222

143

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Abstract Do web surveys still yield lower response rates compared with other survey modes? To answer this question, we replicated and extended a meta-analysis done in 2008 which found that, based on 45 experimental comparisons, web surveys had an 11 percentage points lower response rate compared with other survey modes. Fundamental changes in internet accessibility and use since the publication of the original meta-analysis would suggest that people’s propensity to participate in web surveys has changed considerably in the meantime. However, in our replication and extension study, which comprised 114 experimental comparisons between web and other survey modes, we found almost no change: web surveys still yielded lower response rates than other modes (a difference of 12 percentage points in response rates). Furthermore, we found that prenotifications, the sample recruitment strategy, the survey’s solicitation mode, the type of target population, the number of contact attempts, and the country in which the survey was conducted moderated the magnitude of the response rate differences. These findings have substantial implications for web survey methodology and operations.

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Section: Introductionmentioning

confidence: 99%

Web Versus Other Survey Modes: An Updated and Extended Meta-Analysis Comparing Response Rates

Daikeler

Bošnjak

Manfreda

2019

Journal of Survey Statistics and Methodology

222

143

View full text Add to dashboard Cite

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Total Bias in Income Surveys when Nonresponse and Measurement Errors are Correlated

Neri,

Porreca

2023

Journal of Survey Statistics and Methodology

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Household surveys on income might suffer from quality limitations mainly due to the difficulty of enrolling households (unit nonresponse) and retrieving correct information during the interview (measurement error [ME]). These errors are likely to be correlated because of latent factors, such as the threat of disclosing personal information, the perceived sensitivity of the topic, or social desirability. For survey organizations, assessing the interplay of these errors and their impact on the accuracy and precision of inferences derived from their data is crucial. In this article, we propose to use a standard sample selection model within a total survey error framework to deal with the case of correlated nonresponse error (NR) and ME in estimating average household income. We use it to study the correlation between the two errors, quantify the ME component due to this correlation, and evaluate ME among nonrespondents. Using the Italian Survey on Income and Wealth linked with administrative income data from tax returns, we find a positive correlation between the two errors and that households at the extremes of the income distribution mainly cause this association. Our results show that ME contributes more to the total error than unit nonresponse and that it would be larger in absence of the correlation between the two errors. Finally, efforts to reduce nonresponse rates are worthwhile only for nonrespondents in the lowest estimated response propensity group. If these households participate, the bias decreases because of the reduction in NR that offsets the increase in ME.

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A Meta-Analysis of How Country-Level Factors Affect Web Survey Response Rates

Daikeler

Silber

Bošnjak

2021

International Journal of Market Research

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A major challenge in web-based cross-cultural data collection is varying response rates, which can result in low data quality and non-response bias. Country-specific factors such as the political and demographic, economic, and technological factors as well as the socio-cultural environment may have an effect on the response rates to web surveys. This study evaluates web survey response rates using meta-analytical methods based on 110 experimental studies from seven countries. Three dependent variables, so-called effect sizes, are used: the web response rate, the response rate to the comparison survey mode, and the difference between the two response rates. The meta-analysis indicates that four country-specific factors (political and demographic, economic, technological, and socio-cultural) impact the magnitude of web survey response rates. Specifically, web surveys achieve high response rates in countries with high population growth, high internet coverage, and a high survey participation propensity. On the other hand, web surveys are at a disadvantage in countries with a high population age and high cell phone coverage. This study concludes that web surveys can be a reliable alternative to other survey modes due to their consistent response rates and are expected to be used more frequently in national and international settings.

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The Effect of Nonresponse and Measurement Error on Wage Regression across Survey Modes

Cited by 3 publications

References 40 publications

Web Versus Other Survey Modes: An Updated and Extended Meta-Analysis Comparing Response Rates

Web Versus Other Survey Modes: An Updated and Extended Meta-Analysis Comparing Response Rates

Total Bias in Income Surveys when Nonresponse and Measurement Errors are Correlated

A Meta-Analysis of How Country-Level Factors Affect Web Survey Response Rates

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