[AAPOR (The American Association for Public Opinion Research). 2015. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys, 8th edition. Oakbrook Terrace, IL: AAPOR.]Search in Google Scholar
[Amaya, A., P. Biemer, and D. Kinyon. 2017. “Total Error in a Big Data World with Applications to the Residential Energy Consumption Survey.” Presented at the American Association for Public Opinion Research Annual Conference, New Orleans, LA.]Search in Google Scholar
[Biemer, P. 2010. “Total Survey Error: Design, Implementation, and Evaluation.” Public Opinion Quarterly 74(5): 817–848. Doi: https://doi.org/10.1093/poq/nfq058.10.1093/poq/nfq058]Open DOISearch in Google Scholar
[Biemer, P., K.H. Harris, B. Burke, K. Considine, C. Halpern, and C. Suchindran. 2017a. “Transitioning an In-Person Longitudinal Survey to a Mixed-Mode, Two-Phase Survey Design: Preliminary Results.” Presented at the Annual Conference of the American Association for Public Opinion Research. New Orleans, LA.]Search in Google Scholar
[Biemer, P., J. Murphy, S. Zimmer, C. Berry, G. Deng, and K. Lewis. 2017b. “Using Bonus Monetary Incentives to Encourage Web Response in Mixed-Mode Household Surveys.” Journal of Survey Statistics and Methodology. Doi: https://doi.org/10.1093/jssam/smx015.10.1093/jssam/smx015]Open DOISearch in Google Scholar
[Breyfogle, F. 2003. Implementing Six Sigma: Smarter Solutions Using Statistical Methods. Hoboken, NJ: John Wiley & Sons.]Search in Google Scholar
[Camoes, J. 2008. How to Create a Thematic Map in Excel. Available at: http://www.excelcharts.com/blog/how-to-create-thematic-map-excel/ (accessed November 26, 2017).]Search in Google Scholar
[Chun, A.Y., B. Schouten, and J. Wagner. 2017. “JOS Special Issue on Responsive and Adaptive Survey Design: Looking Back to See Forward – Editorial.” Journal of Official Statistics 33(3): 571–577. Doi: http://dx.doi.org/10.1515/JOS-2017-0027.10.1515/JOS-2017-0027]Open DOISearch in Google Scholar
[Cleveland, W. 1993. Visualizing Data. Summit, NJ: Hobart Press.]Search in Google Scholar
[Cramér, H. 1946. Mathematical Methods of Statistics. Princeton: Princeton University Press.10.1515/9781400883868]Search in Google Scholar
[Dillman, D., J.D. Smyth, and L.M. Christian. 2014. Internet, Phone, and Mail, and Mixed-Mode Surveys: The Tailored Design Method, 4th Edition. Hoboken, NJ: Wiley.]Search in Google Scholar
[Dillman, D.A. and M.L. Edwards. 2016. “Designing a Mixed-Mode Survey.” In Wolfe, Christof, Joye, Dominique, Smith, Tom W. and Fu, Yang-chih, Sage Handbook of Survey Methodology. Sage Publications Wolf, Joye, Smith and Fu. Thousand Oaks. CA, 255–268.]Search in Google Scholar
[Duprey, M., J. Murphy, P. Biemer, and R. Chew. 2017. “Veni, Vidi, Vici: Interactive Data Visualizations for Adaptive Total Design.” Presented at the 5th Workshop on Adaptive and Responsive Survey Design. Ann Arbor, MI.]Search in Google Scholar
[Eddy, W.F. and Marton, K., Editors. 2012. Effective Tracking of Building Energy Use: Improving the Commercial Buildings and Residential Energy Consumption Surveys. Washington D.C.: The National Academies Press.]Search in Google Scholar
[Edgar, J., J. Murphy, and M. Keating. 2016. “Comparing Traditional and Crowdsourcing Methods for Pretesting Survey Questions.” SAGE Open 6(4): 1–14. Doi: https://doi.org/10.1177/2158244016671770.10.1177/2158244016671770]Open DOISearch in Google Scholar
[Groves, R.M. 1989. Survey Errors and Survey Costs. New York: Wiley.10.1002/0471725277]Search in Google Scholar
[Groves, R. and S. Heeringa. 2006. “Responsive Design for Household Surveys: Tools for Actively Controlling Survey Errors and Costs.” Journal of the Royal Statistical Society, Series A 169(3): 439–457. Doi: http://dx.doi.org/10.1111/j.1467-985X.2006.00423.x.10.1111/j.1467-985X.2006.00423.x]Open DOISearch in Google Scholar
[Hardin, M., D. Horn, R. Perez, and L. Williams. 2012. “Which Chart or Graph is Right for You? Telling Impactful Stories with Data.” Tableau Software. Available at: http://theathenaforum.org/sites/default/files/WHich%20chart%20is%20right%20for%20you.pdf (accessed November 26, 2017).]Search in Google Scholar
[Hornbaek, K. and E. Frokjaer. 2003. “Reading Patterns and Usability in Visualizations of Electronic Documents.” ACM Transactions on Computer-Human Interaction 10(2): 119–149. Doi: https://doi.org/10.1145/772047.772050.10.1145/772047.772050]Open DOISearch in Google Scholar
[Howden, L., S. Joestl, and R. Cohen. 2015. Improving Response Rates using a Mixed-Mode Approach: Results from the National Health Care Interview Survey. Presented at the 2015 FedCASIC Conference. Available at: https://www.census.gov/fedcasic/fc2015/ppt/27_howden.pdf (accessed November 21, 2017).]Search in Google Scholar
[Kahneman, D. 2011. Thinking Fast and Slow. New York: Farrar, Straus, and Giroux.]Search in Google Scholar
[Laflamme, F. and J. Wagner. 2016. “Responsive and Adaptive Designs.” In The SAGE Handbook of Survey Methodology, edited by C. Wolf, D. Joye, T. Smith, and Y. Fu. Los Angeles: Sage.10.4135/9781473957893.n26]Search in Google Scholar
[Link, M. and A. Mokdad. 2005. “Alternative Modes for Health Surveillance Surveys: an Experiment with Web, Mail, and Telephone.” Epidemiology 16: 701–704. Doi: 10.1097/01.ede.0000172138.67080.7f.10.1097/01.ede.0000172138.67080.7f16135951]Open DOISearch in Google Scholar
[Luiten, A. and B. Schouten. 2013. “Tailored Fieldwork Design to Increase Representative Household Survey Response: an Experiment in the Survey of Consumer Satisfaction.” Journal of the Royal Statistical Society A 176: 169–189. Doi: https://doi.org/10.1111/j.1467-985X.2012.01080.x.10.1111/j.1467-985X.2012.01080.x]Open DOISearch in Google Scholar
[Morganstein, D.R. and D.A. Marker. 1997. “Continuous Quality Improvement in Statistical Agencies.” In Survey Measurement and Process Quality, edited by L.E. Lyberg, P. Biemer, M. Collins, E.D. de Leeuw, C. Dippo, N. Schwarz, and D. Trewin. (pp. 475–500). New York: John Wiley & Sons.]Search in Google Scholar
[Murphy, J., D. Mayclin, A. Richards, and D. Roe. 2016. “A Multi-method Approach to Survey Pretesting.” In 2015 FCSM Research Conference Proceedings. Available at: https://fcsm.sites.usa.gov/files/2016/03/D3_Murphy_2015FCSM.pdf. (accessed November 26, 2017).]Search in Google Scholar
[Murphy, J., P. Biemer, M. Duprey, and R. Chew. 2017. “Interactive Adaptive Total Design Reports for Near Real-Time Survey Monitoring.” Presented at the 2017 Conference of the European Survey Research Association. Lisbon, Portugal.]Search in Google Scholar
[Schouten, B., F. Cobben, and J. Bethlehem. 2009. “Indictators of Representativeness of Survey Nonresponse.” Survey Methodology 35: 101–113.]Search in Google Scholar
[Schouten, B., A. Peytchev, and J. Wagner. 2017. Adaptive Survey Design. Boca Raton, FL: Chapman and Hall/CRC.10.1201/9781315153964]Search in Google Scholar
[Tufte, E. 2001. The Visual Display of Quantitative Information (2nd ed.). Cheshire, CT: Graphics Press. ISBN 0-9613921-4-2.]Search in Google Scholar
[U.S. Census Bureau. 2015. American Community Survey (ACS) 2014 Data Release New and Noteable. Available at: https://www.census.gov/programs-surveys/acs/news/data-releases/2014/release.html#par_textimage_12. (accessed November 21, 2017).]Search in Google Scholar
[Zimmer, S., P. Biemer, P. Kott, and C. Berry. 2016. “Testing a Model-Directed, Mixed Mode Protocol in the RECS Pilot Study.” In 2015 FCSM Research Conference Proceedings. Available at: https://s3.amazonaws.com/sitesusa/wp-content/uploads/sites/242/2016/03/G2_Zimmer_2015FCSM.pdf. (accessed November 26, 2017).]Search in Google Scholar