The Experts below are selected from a list of 12270 Experts worldwide ranked by ideXlab platform
James P Ziliak - One of the best experts on this subject based on the ideXlab platform.
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trouble in the tails what we know about earnings Nonresponse thirty years after lillard smith and welch
Journal of Political Economy, 2019Co-Authors: Christopher R Bollinger, Barry T Hirsch, Charles Hokayem, James P ZiliakAbstract:Earnings Nonresponse in household surveys is widespread, yet there is limited knowledge of how Nonresponse biases earnings measures. We examine the consequences of Nonresponse on earnings gaps and ...
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trouble in the tails what we know about earnings Nonresponse thirty years after lillard smith and welch
Social Science Research Network, 2018Co-Authors: Christopher R Bollinger, Barry T Hirsch, Charles Hokayem, James P ZiliakAbstract:Earnings Nonresponse in household surveys is widespread, yet there is limited knowledge of how Nonresponse biases earnings measures. We examine the consequences of Nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings data. The common assumption that earnings are missing at random is rejected. Nonresponse across the earnings distribution is U-shaped, highest in the left and right tails. Inequality measures differ between household and administrative data due in part to Nonresponse. Nonresponse biases earnings differentials by race, gender, and education, particularly in the tails. Flexible copula-based models can account for nonrandom Nonresponse.
Denise E Wilfley - One of the best experts on this subject based on the ideXlab platform.
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pretreatment and process predictors of outcome in interpersonal and cognitive behavioral psychotherapy for binge eating disorder
Journal of Consulting and Clinical Psychology, 2007Co-Authors: Anja Hilbert, Brian E Saelens, Richard I Stein, Danyte S Mockus, Robinson R Welch, Georg E Matt, Denise E WilfleyAbstract:The present study examined pretreatment and process predictors of individual Nonresponse to psychological group treatment of binge eating disorder (BED). In a randomized trial, 162 overweight patients with BED were treated with either group cognitive-behavioral therapy or group interpersonal psychotherapy. Treatment Nonresponse, which was defined as nonabstinence from binge eating, was assessed at posttreatment and at 1 year following treatment completion. Using 4 signal detection analyses, greater extent of interpersonal problems prior to treatment or at midtreatment were identified as predictors of Nonresponse, both at posttreatment and at 1-year follow-up. Greater pretreatment and midtreatment concerns about shape and weight, among those patients with low interpersonal problems, were predictive of posttreatment Nonresponse. Lower group cohesion during the early treatment phase predicted Nonresponse at 1-year follow-up. Attention to specific pre- or intreatment predictors could allow for targeted selection into differential or augmented care and could thus improve response to group psychotherapy for BED.
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pretreatment and process predictors of outcome in interpersonal and cognitive behavioral psychotherapy for binge eating disorder
Journal of Consulting and Clinical Psychology, 2007Co-Authors: Anja Hilbert, Brian E Saelens, Richard I Stein, Danyte S Mockus, Robinson R Welch, Georg E Matt, Denise E WilfleyAbstract:Abstract The present study examined pretreatment and process predictors of individual Nonresponse to psychological group treatment of binge eating disorder (BED). In a randomized trial, 162 overweight patients with BED were treated with either group cognitive-behavioral therapy or group interpersonal psychotherapy. Treatment Nonresponse, which was defined as nonabstinence from binge eating, was assessed at posttreatment and at 1 year following treatment completion. Using 4 signal detection analyses, greater extent of interpersonal problems prior to treatment or at midtreatment were identified as predictors of Nonresponse, both at posttreatment and at 1-year follow-up. Greater pretreatment and midtreatment concerns about shape and weight, among those patients with low interpersonal problems, were predictive of posttreatment Nonresponse. Lower group cohesion during the early treatment phase predicted Nonresponse at 1-year follow-up. Attention to specific pre- or intreatment predictors could allow for targeted selection into differential or augmented care and could thus improve response to group psychotherapy for BED.
Barry T Hirsch - One of the best experts on this subject based on the ideXlab platform.
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trouble in the tails what we know about earnings Nonresponse thirty years after lillard smith and welch
Journal of Political Economy, 2019Co-Authors: Christopher R Bollinger, Barry T Hirsch, Charles Hokayem, James P ZiliakAbstract:Earnings Nonresponse in household surveys is widespread, yet there is limited knowledge of how Nonresponse biases earnings measures. We examine the consequences of Nonresponse on earnings gaps and ...
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trouble in the tails what we know about earnings Nonresponse thirty years after lillard smith and welch
Social Science Research Network, 2018Co-Authors: Christopher R Bollinger, Barry T Hirsch, Charles Hokayem, James P ZiliakAbstract:Earnings Nonresponse in household surveys is widespread, yet there is limited knowledge of how Nonresponse biases earnings measures. We examine the consequences of Nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings data. The common assumption that earnings are missing at random is rejected. Nonresponse across the earnings distribution is U-shaped, highest in the left and right tails. Inequality measures differ between household and administrative data due in part to Nonresponse. Nonresponse biases earnings differentials by race, gender, and education, particularly in the tails. Flexible copula-based models can account for nonrandom Nonresponse.
Roger Tourangeau - One of the best experts on this subject based on the ideXlab platform.
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Responsive Survey Designs for Reducing Nonresponse Bias
Journal of Official Statistics, 2017Co-Authors: J. Michael Brick, Roger TourangeauAbstract:Survey researchers have been investigating alternative approaches to reduce data collection costs while mitigating the risk of Nonresponse bias or to produce more accurate estimates within the same budget. Responsive or adaptive design has been suggested as one means for doing this. Falling survey response rates and the need to find effective ways of implementing responsive design has focused attention on the relationship between response rates and Nonresponse bias. In our article, we re-examine the data compiled by Groves and Peytcheva (2008) in their influential article and show there is an important between-study component of variance in addition to the within-study variance highlighted in the original analysis. We also show that theory implies that raising response rates can help reduce the Nonresponse bias on average across the estimates within a study. We then propose a typology of response propensity models that help explain the empirical findings, including the relative weak relationship between Nonresponse rates and Nonresponse bias. Using these results, we explore when responsive design tools such as switching modes, giving monetary incentives, and increasing the level of effort are likely to be effective. We conclude with some comments on the use of responsive design and weighting to control Nonresponse bias.
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where do we go from here Nonresponse and social measurement
Annals of The American Academy of Political and Social Science, 2013Co-Authors: Douglas S Massey, Roger TourangeauAbstract:Surveys undergird government statistical systems and social scientific research throughout the world. Rates of Nonresponse are rising in cross-sectional surveys (those conducted during a fixed period of time and not repeated). Although this trend worries those concerned with the validity of survey data, there is no necessary relationship between the rate of Nonresponse and the degree of bias. A high rate of Nonresponse merely creates the potential for bias, but the degree of bias depends on how factors promoting Nonresponse are related to variables of interest. Nonresponse can be reduced by offering financial incentives to respondents and by careful design before entering the field, creating a trade-off between cost and potential bias. When bias is suspected, it can be countered by weighting individual cases by the inverse of their response propensity. Response propensities are typically estimated using a logistic regression equation to predict the dichotomous outcome of survey participation as a function...
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Nonresponse error measurement error and mode of data collection tradeoffs in a multi mode survey of sensitive and non sensitive items
Public Opinion Quarterly, 2010Co-Authors: Joseph W Sakshaug, Ting Yan, Roger TourangeauAbstract:Although some researchers have suggested that a tradeoff exists between Nonresponse and measurement error, to date, the evidence for this connection has been relatively sparse. We examine data from an alumni survey to explore potential links between Nonresponse and mea- surement error. Records data were available for some of the survey items, allowing us to check the accuracy of the answers. The survey included relatively sensitive questions about the respondent's academic perfor- mance and compared three methods of data collection—computer-assisted telephone interviewing (CATI), interactive voice response (IVR), and an Internet survey. We test the hypothesis that the two modes of computerized self-administration reduce measurement error but increase Nonresponse error, in particular the Nonresponse error associated with dropping out of the survey during the switch from the initial telephone contact to the IVR or Internet mode. We find evidence for relatively large errors due to the mode switch; in some cases, these mode switch biases offset the advantages of self-administration for reducing measurement error. We find less evidence for a possible second link between Nonresponse and measurement error, based on a relationship between the level of effort needed to obtain the data and the accuracy of the data that are ultimately obtained. We also compare Nonresponse and measurement errors across different types of sensitive items; in general, measurement error tended to be the largest source of error for estimates of socially undesirable
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Experiments in Producing Nonresponse Bias
Public Opinion Quarterly, 2006Co-Authors: Robert M. Groves, Stanley Presser, Roger Tourangeau, Mick P. Couper, Eleanor Singer, Giorgina Piani Acosta, Lindsay D. NelsonAbstract: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 arises from the presence of a covariance between response propensity and the survey variables of interest. To understand the covariance term, researchers must think about the common influences on response propensity and the survey variable. Three variables appear to be especially relevant in this regard: interest in the survey topic, reactions to the survey sponsor, and the use of incentives. A set of randomized experiments tests whether those likely to be interested in the stated survey topic participate at higher rates and whether Nonresponse bias on estimates involving vari- ables central to the survey topic is affected by this. The experiments also test whether incentives disproportionately increase the participation of those less interested in the topic. The experiments show mixed results in support of these key hypotheses.
Christopher R Bollinger - One of the best experts on this subject based on the ideXlab platform.
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trouble in the tails what we know about earnings Nonresponse thirty years after lillard smith and welch
Journal of Political Economy, 2019Co-Authors: Christopher R Bollinger, Barry T Hirsch, Charles Hokayem, James P ZiliakAbstract:Earnings Nonresponse in household surveys is widespread, yet there is limited knowledge of how Nonresponse biases earnings measures. We examine the consequences of Nonresponse on earnings gaps and ...
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trouble in the tails what we know about earnings Nonresponse thirty years after lillard smith and welch
Social Science Research Network, 2018Co-Authors: Christopher R Bollinger, Barry T Hirsch, Charles Hokayem, James P ZiliakAbstract:Earnings Nonresponse in household surveys is widespread, yet there is limited knowledge of how Nonresponse biases earnings measures. We examine the consequences of Nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings data. The common assumption that earnings are missing at random is rejected. Nonresponse across the earnings distribution is U-shaped, highest in the left and right tails. Inequality measures differ between household and administrative data due in part to Nonresponse. Nonresponse biases earnings differentials by race, gender, and education, particularly in the tails. Flexible copula-based models can account for nonrandom Nonresponse.
