TY  - JOUR
T1  - Dynamic Question Ordering in Online Surveys
JF  - Journal of Official Statistics
Y1  - 2017
A1  - Early, Kirstin
A1  - Mankoff, Jennifer
A1  - Fienberg, Stephen E.
AB  - Online surveys have the potential to support adaptive questions, where later questions depend on earlier responses. Past work has taken a rule-based approach, uniformly across all respondents. We envision a richer interpretation of adaptive questions, which we call dynamic question ordering (DQO), where question order is personalized. Such an approach could increase engagement, and therefore response rate, as well as imputation quality. We present a DQO framework to improve survey completion and imputation. In the general survey-taking setting, we want to maximize survey completion, and so we focus on ordering questions to engage the respondent and collect hopefully all information, or at least the information that most characterizes the respondent, for accurate imputations. In another scenario, our goal is to provide a personalized prediction. Since it is possible to give reasonable predictions with only a subset of questions, we are not concerned with motivating users to answer all questions. Instead, we want to order questions to get information that reduces prediction uncertainty, while not being too burdensome. We illustrate this framework with an example of providing energy estimates to prospective tenants. We also discuss DQO for national surveys and consider connections between our statistics-based question-ordering approach and cognitive survey methodology.
VL  - 33
IS  - 3
ER  - 

TY  - ABST
T1  - Sequential Prediction of Respondent Behaviors Leading to Error in Web-based Surveys
Y1  - 2017
A1  - Eck, Adam
A1  - Soh, Leen-Kiat
ER  - 

TY  - ABST
T1  - Data management and analytic use of paradata: SIPP-EHC audit trails
Y1  - 2016
A1  - Lee, Jinyoung
A1  - Seloske, Ben
A1  - Córdova Cazar, Ana Lucía
A1  - Eck, Adam
A1  - Kirchner, Antje
A1  - Belli, Robert F.
ER  - 

TY  - CONF
T1  - Changing ‘Who’ or ‘Where’: Implications for Data Quality in the American Time Use Survey
T2  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
Y1  - 2015
A1  - Deal, C.E.
A1  - Kirchner, A.
A1  - Cordova-Cazar, A.L.
A1  - Ellyne, L.
A1  - Belli, R.F.
JF  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
CY  - Hollywood, Florida
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - CONF
T1  - Determining Potential for Breakoff in Time Diary Survey Using Paradata
T2  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
Y1  - 2015
A1  - Wettlaufer, D.
A1  - Arunachalam, H.
A1  - Atkin, G.
A1  - Eck, A.
A1  - Soh, L.-K.
A1  - Belli, R.F.
JF  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
CY  - Hollywood, Florida
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - CONF
T1  - I Know What You Did Next: Predicting Respondent’s Next Activity Using Machine Learning
T2  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
Y1  - 2015
A1  - Arunachalam, H.
A1  - Atkin, G.
A1  - Eck, A.
A1  - Wettlaufer, D.
A1  - Soh, L.-K.
A1  - Belli, R.F.
JF  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
CY  - Hollywood, Florida
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - RPRT
T1  - NCRN Meeting Fall 2016: Dynamic Question Ordering: Obtaining Useful Information While Reducing Burden
Y1  - 2015
A1  - Early, Kirstin
AB  - NCRN Meeting Fall 2016: Dynamic Question Ordering: Obtaining Useful Information While Reducing Burden Early, Kirstin
PB  - Carnegie-Mellon University
UR  - http://hdl.handle.net/1813/45822
ER  - 

TY  - CONF
T1  - Predicting Breakoff Using Sequential Machine Learning Methods
T2  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
Y1  - 2015
A1  - Soh, L.-K.
A1  - Eck, A.
A1  - McCutcheon, A.L.
JF  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
CY  - Hollywood, Florida
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - JOUR
T1  - Understanding the Dynamics of $2-a-Day Poverty in the United States
JF  - The Russell Sage Foundation Journal of the Social Sciences
Y1  - 2015
A1  - Shaefer, H. Luke
A1  - Edin, Kathryn
A1  - Talbert, E.
VL  - 1
IS  - Severe Deprivation
ER  - 

TY  - JOUR
T1  - Understanding the Human Condition through Survey Informatics
JF  - IEEE Computer
Y1  - 2015
A1  - Eck, A.
A1  - Leen-Kiat, S.
A1  - McCutcheon, A. L.
A1  - Smyth, J.D.
A1  - Belli, R.F.
VL  - 48
IS  - 11
ER  - 

TY  - CONF
T1  - Using Machine Learning Techniques to Predict Respondent Type from A Priori Demographic Information
T2  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
Y1  - 2015
A1  - Atkin, G.
A1  - Arunachalam, H.
A1  - Eck, A.
A1  - Wettlaufer, D.
A1  - Soh, L.-K.
A1  - Belli, R.F.
JF  - 70th Annual Conference of the American Association for Public Opinion Research (AAPOR)
CY  - Hollywood, Florida
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - CONF
T1  - Designing an Intelligent Time Diary Instrument: Visualization, Dynamic Feedback, and Error Prevention and Mitigation
T2  - UNL/SRAM/Gallup Symposium
Y1  - 2014
A1  - Atkin, G.
A1  - Arunachalam, H.
A1  - Eck, A.
A1  - Soh, L.-K.
A1  - Belli, R.F.
JF  - UNL/SRAM/Gallup Symposium
CY  - Omaha, NE
UR  - http://grc.unl.edu/unlsramgallup-symposium
ER  - 

TY  - CONF
T1  - Designing an Intelligent Time Diary Instrument: Visualization, Dynamic Feedback, and Error Prevention and Mitigation
T2  - American Association for Public Opinion Research 2014 Annual Conference
Y1  - 2014
A1  - Atkin, G.
A1  - Arunachalam, H.
A1  - Eck, A.
A1  - Soh, L.-K.
A1  - Belli, R.
JF  - American Association for Public Opinion Research 2014 Annual Conference
CY  - Anaheim, CA.
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - CONF
T1  - Making sense of paradata: Challenges faced and lessons learned
T2  - American Association for Public Opinion Research 2014 Annual Conference
Y1  - 2014
A1  - Eck, A.
A1  - Stuart, L.
A1  - Atkin, G.
A1  - Soh, L-K
A1  - McCutcheon, A.L.
A1  - Belli, R.F.
JF  - American Association for Public Opinion Research 2014 Annual Conference
CY  - Anaheim, CA
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - CONF
T1  - Making Sense of Paradata: Challenges Faced and Lessons Learned
T2  - UNL/SRAM/Gallup Symposium
Y1  - 2014
A1  - Eck, A.
A1  - Stuart, L.
A1  - Atkin, G.
A1  - Soh, L-K
A1  - McCutcheon, A.L.
A1  - Belli, R.F.
JF  - UNL/SRAM/Gallup Symposium
CY  - Omaha, NE
UR  - http://grc.unl.edu/unlsramgallup-symposium
ER  - 

TY  - CONF
T1  - Survey Informatics: Ideas, Opportunities, and Discussions
T2  - UNL/SRAM/Gallup Symposium
Y1  - 2014
A1  - Eck, A.
A1  - Soh, L-K
JF  - UNL/SRAM/Gallup Symposium
CY  - Omaha, NE
UR  - http://grc.unl.edu/unlsramgallup-symposium
ER  - 

TY  - JOUR
T1  - Top-Coding and Public Use Microdata Samples from the U.S. Census Bureau
JF  - Journal of Privacy and Confidentiality
Y1  - 2014
A1  - Crimi, N.
A1  - Eddy, W. C.
VL  - 6
UR  - http://repository.cmu.edu/jpc/vol6/iss2/2/
ER  - 

TY  - CONF
T1  - Examining the relationship between error and behavior in the American Time Use Survey using audit trail paradata
T2  - American Association for Public Opinion Research 2013 Annual Conference
Y1  - 2013
A1  - Ruther, N.
A1  - T. Al Baghal
A1  - A. Eck
A1  - L. Stuart
A1  - L. Phillips
A1  - R. Belli
A1  - Soh, L-K
JF  - American Association for Public Opinion Research 2013 Annual Conference
CY  - Boston, MA
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - JOUR
T1  - Rising extreme poverty in the United States and the response of means-tested transfers.
JF  - Social Service Review
Y1  - 2013
A1  - H. Luke Shaefer
A1  - Edin, K.
AB  - This study documents an increase in the prevalence of extreme poverty among US households with children between 1996 and 2011 and assesses the response of major federal means-tested transfer programs. Extreme poverty is defined using a World Bank metric of global poverty: \$2 or less, per person, per day. Using the 1996–2008 panels of the Survey of Income and Program Participation (SIPP), we estimate that in mid-2011, 1.65 million households with 3.55 million children were living in extreme poverty in a given month, based on cash income, constituting 4.3 percent of all nonelderly households with children. The prevalence of extreme poverty has risen sharply since 1996, particularly among those most affected by the 1996 welfare reform. Adding SNAP benefits to household income reduces the number of extremely poor households with children by 48.0 percent in mid-2011. Adding SNAP, refundable tax credits, and housing subsidies reduces it by 62.8 percent.
VL  - 87
UR  - http://www.jstor.org/stable/10.1086/671012
IS  - 2
ER  - 

TY  - CONF
T1  - What are you doing now?: Audit trails, Activity level responses and error in the American Time Use Survey
T2  - American Association for Public Opinion Research
Y1  - 2013
A1  - T. Al Baghal
A1  - Phillips, A.L.
A1  - Ruther, N.
A1  - Belli, R.F.
A1  - Stuart, L.
A1  - Eck, A.
A1  - Soh, L-K
JF  - American Association for Public Opinion Research
CY  - Boston, MA
UR  - http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx
ER  - 

TY  - ABST
T1  - Extreme Poverty in the United States, 1996 to 2011
Y1  - 2012
A1  - Shaefer, H. Luke
A1  - Edin, Kathryn
PB  - University of Michigan
UR  - http://www.npc.umich.edu/publications/policy_briefs/brief28/policybrief28.pdf
N1  - NCRN
ER  - 

TY  - ABST
T1  - Working with the SIPP-EHC audit trails:  Parallel and sequential retrieval
Y1  - 0
A1  - Lee, Jinyoung
A1  - Seloske, Ben
A1  - Córdova Cazar, Ana Lucía
A1  - Eck, Adam
A1  - Belli, Robert F.
ER  -