Professor Joseph Sakshaug
Functions at the IAB
Professional background
Joseph Sakshaug is distinguished researcher, deputy head of research, and head of the Data Collection and Data Integration Unit in the Statistical Methods Research Department at the IAB. He is also university professor of statistics at the School of Mathematics, Computer Science, and Statistics at the LMU Munich (Ludwig-Maximilians-Universität München) and honorary full professor at the School of Social Sciences at the University of Mannheim. Previously, he was associate professor (senior lecturer) in Social Statistics at the University of Manchester (UK), and assistant professor (junior professor) of Statistics and Social Science Methodology at the University of Mannheim (Germany). Mr Sakshaug received his MSc and PhD in Survey Methodology from the University of Michigan-Ann Arbor, and his BA in Mathematics from the University of Washington-Seattle. From 2011 to 2013, he was an Alexander von Humboldt postdoctoral research fellow at the IAB and the LMU Munich. He is also a faculty member in the International Program in Survey and Data Science, and an adjunct research assistant professor at the Survey Research Center of the Institute for Social Research at the University of Michigan. His research focuses on data quality issues in complex surveys, the integration of multiple data sources, and empirical research methods.
Activities
Projects
ongoing Projects
- Ideal Survey Design in Establishment Panels
- Item Nonresponse in Factorial Survey Experiments - Simulation Study
- To Switch or Not to Switch. An Analysis on Switching Modes Mid-Interview in Establishment Surveys
- More Interviews = More Panel Attrition? An Analysis on the Implementation and Effects of Supplement Surveys.
- Does the Mode Really Matter? Mode Effects in Factorial Survey Experiments.
- Preparation of a handbook article on survey methodology for establishment surveys
- LPP-Modusexperiment Wellen 6/7
- Investigating Measurement Error in a Mixed-Mode Establishment Survey
- The effect of interview audio recordings on interviewer behavior
- Analyse des Moduseffektes auf den Total Survey Error in der IAB-Stellenerhebung
- Paradaten-Betriebspanel
- Data quality of the "Expectations towards Economy and Society" panel
finished Projects
- Qualitative focus group discussion: from first conact to interviewing establishments
- Identification of Partial Falsifications in Panel Surveys
- Analyse der Selektivität der Respondenten in der IAB-Stellenerhebung in der COVID-19 Pandemie
- Identifikation von Interviewer Fälschungen mittels maschinellen Lernens
- Developing an automated method to identify deviant interviewers
- Modeexperiments within the IAB-Job Vacancy Survey
- Cross-sectional and longitudinal nonresponse analysis in the IAB Establishment Panel 2001-2017
- Verhalten von Interviewern in besonderen Interviewsituationen
- Analyse der Unit Non-Response der IAB-Stellenerhebung
- IAB-Betriebspanel: Stichprobenziehung und Gewichtung
- Analysis of mixed-mode experiment 2018 over time
- Experiment Interviewer Training
- LPP Mode Experiment
- Anschreiben-Framing und Bereitschaft zur Studienteilnahme
- Improving data quality: statistical identification of fraudulent interviews
- Umstellung des IAB-Betriebspanels auf computergestützte Datenerfassung: Modus-Experiment
- Mode of invitation in a web survey of establishments
- Imputation and record linkage strategies for educational data collected from surveys and administrative sources
- Placement of the Linkage Consent Question in an Establishment Survey
- Imputation und Gewichtung zum Umgang mit fehlenden Werten in hierarchischen Längsschnitterhebungen
- Nonresponse Follow-Up Study to Filterfragen Survey
- Linkage consent in the total survey error perspective
Publications
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The Impact of Mail, Web, and Mixed-Mode Data Collection on Participation in Establishment Surveys
Küfner, B., Sakshaug, J., Zins, S. & Globisch, C. (2024): The Impact of Mail, Web, and Mixed-Mode Data Collection on Participation in Establishment Surveys. In: Journal of survey statistics and methodology. DOI:10.1093/jssam/smae033
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Bayesian Integration of Probability and Nonprobability Samples for Logistic Regression
Salvatore, C., Biffignandi, S., Sakshaug, J., Wiśniowski, A. & Struminskaya, B. (2024): Bayesian Integration of Probability and Nonprobability Samples for Logistic Regression. In: Journal of survey statistics and methodology, Vol. 12, No. 2, p. 458-492., accepted on October 03, 2023. DOI:10.1093/jssam/smad041
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Interviewer Effects on the Measurement of Physical Performance in a Cross-National Biosocial Survey
Waldmann, S., Sakshaug, J. & Cernat, A. (2024): Interviewer Effects on the Measurement of Physical Performance in a Cross-National Biosocial Survey. In: Journal of survey statistics and methodology, Vol. 12, No. 4, p. 961-986., accepted on July 14, 2023. DOI:10.1093/jssam/smad031
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Nonresponse trends in establishment panel surveys: findings from the 2001–2017 IAB establishment panel
König, C. & Sakshaug, J. (2023): Nonresponse trends in establishment panel surveys: findings from the 2001–2017 IAB establishment panel. In: Journal for labour market research, Vol. 57. DOI:10.1186/s12651-023-00349-4
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To Link or Synthesize? An Approach to Data Quality Comparison
Smith, D., Elliot, M. & Sakshaug, J. (2023): To Link or Synthesize? An Approach to Data Quality Comparison. In: Journal of Data and Information Quality, Vol. 15, No. 2, p. 1-20. DOI:10.1145/3580487
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Ethical Considerations for Augmenting Surveys with Auxiliary Data Sources
Struminskaya, B. & Sakshaug, J. (2023): Ethical Considerations for Augmenting Surveys with Auxiliary Data Sources. In: Public opinion quarterly, Vol. 87, No. S1, p. 619-633., accepted on April 21, 2023. DOI:10.1093/poq/nfad030
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Augmenting Surveys with Paradata, Administrative Data, and Contextual Data
Sakshaug, J. & Struminskaya, B. (2023): Augmenting Surveys with Paradata, Administrative Data, and Contextual Data. In: Public opinion quarterly, Vol. 87, No. S1, p. 475-479., accepted on April 13, 2023. DOI:10.1093/poq/nfad026
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Recent Advances in Data Integration
Sakshaug, J. & Steorts, R. (2023): Recent Advances in Data Integration. In: Journal of survey statistics and methodology, Vol. 11, No. 3, p. 513-517. DOI:10.1093/jssam/smad009
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Transitioning an employee panel survey from telephone to online and mixed-mode data collection
Mackeben, J. & Sakshaug, J. (2023): Transitioning an employee panel survey from telephone to online and mixed-mode data collection. In: Statistical Journal of the IAOS, Vol. 39, No. 1, p. 213-232., accepted on December 06, 2022. DOI:10.3233/SJI-220088
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Advances in Business Statistics, Methods and Data Collection
Snijkers, G., Bavdaž, M., Bender, S., Jones, J., MacFeely, S., Sakshaug, J., Thompson, K. & Delden, A. (eds.) (2023): Advances in Business Statistics, Methods and Data Collection. Chichester: Wiley, 856 p.
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Recent Findings from Experiments in Establishment Surveys
Langeland, J., Ridolfo, H., McCarthy, J., Ott, K., Kilburg, D., CyBulski, K., Krakowiecki, M., Vittoriano, L., Potts, M., Küfner, B., Sakshaug, J. & Zins, S. (2023): Recent Findings from Experiments in Establishment Surveys. In: G. Snijkers, M. Bavdaž, S. Bender, S. MacFeely, J. Sakshaug, K. J. Thompson & A. v. Delden (Hrsg.) (2023): Advances in Business Statistics, Methods and Data Collection, p. 437-467. DOI:10.1002/9781119672333.ch19
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Effects of mixing modes on nonresponse and measurement error in an economic panel survey
Sakshaug, J., Beste, J. & Trappmann, M. (2023): Effects of mixing modes on nonresponse and measurement error in an economic panel survey. In: Journal for labour market research, Vol. 57, accepted on December 05, 2022. DOI:10.1186/s12651-022-00328-1
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Detecting Interviewer Fraud Using Multilevel Models
Olbrich, L., Kosyakova, Y., Sakshaug, J. & Schwanhäuser, S. (2024): Detecting Interviewer Fraud Using Multilevel Models. In: Journal of survey statistics and methodology, Vol. 12, No. 1, p. 14-35. DOI:10.1093/jssam/smac036
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The Impact of Mixing Survey Modes on Estimates of Change: A Quasi-Experimental Study
Cernat, A. & Sakshaug, J. (2023): The Impact of Mixing Survey Modes on Estimates of Change: A Quasi-Experimental Study. In: Journal of survey statistics and methodology, Vol. 11, No. 5, p. 1110-1132., accepted on October 14, 2022. DOI:10.1093/jssam/smac034
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The Impact of Survey Mode Design and Questionnaire Length on Measurement Quality
Cernat, A., Sakshaug, J., Christmann, P. & Gummer, T. (2024): The Impact of Survey Mode Design and Questionnaire Length on Measurement Quality. In: Sociological methods & research, Vol. 53, No. 4, p. 1873-1904., accepted on August 22, 2022. DOI:10.1177/00491241221140139
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Analysing establishment survey non-response using administrative data and machine learning
Küfner, B., Sakshaug, J. & Zins, S. (2022): Analysing establishment survey non-response using administrative data and machine learning. In: Journal of the Royal Statistical Society. Series A, Statistics in Society, Vol. 185, No. Suppl. 2, p. S310-S342., accepted on July 23, 2022. DOI:10.1111/rssa.12942
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Establishment survey participation during the COVID-19 pandemic
Küfner, B., Sakshaug, J. & Zins, S. (2022): Establishment survey participation during the COVID-19 pandemic. In: Journal for labour market research, Vol. 56, accepted on August 19, 2022. DOI:10.1186/s12651-022-00321-8
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The impact of using the Web in a mixed-mode follow-up of a longitudinal birth cohort study: Evidence from the National Child Development Study
Goodman, A., Brown, M., Silverwood, R., Sakshaug, J., Calderwood, L., Williams, J. & Ploubidis, G. (2022): The impact of using the Web in a mixed-mode follow-up of a longitudinal birth cohort study: Evidence from the National Child Development Study. In: Journal of the Royal Statistical Society. Series A, Statistics in Society, Vol. 185, No. 3, p. 822-850., accepted on November 03, 2021. DOI:10.1111/rssa.12786
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Measurement equivalence in probability and nonprobability online panels
Einarsson, H., Sakshaug, J., Cernat, A., Cornesse, C. & Blom, A. (2022): Measurement equivalence in probability and nonprobability online panels. In: International Journal of Market Research, Vol. 64, No. 4, p. 484-505., accepted on February 08, 2022. DOI:10.1177/14707853221085206
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Measurement Equivalence in Sequential Mixed-Mode Surveys
Sakshaug, J., Cernat, A., Silverwood, R., Calderwood, L. & Ploubidis, G. (2022): Measurement Equivalence in Sequential Mixed-Mode Surveys. In: Survey research methods, Vol. 16, No. 1, p. 29-43., accepted on September 17, 2021. DOI:10.18148/srm/2022.v16i1.7811
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Introducing Web in a Telephone Employee Survey: Effects on Nonresponse and Costs
Mackeben, J. & Sakshaug, J. (2023): Introducing Web in a Telephone Employee Survey: Effects on Nonresponse and Costs. In: Journal of survey statistics and methodology, Vol. 11, No. 5, p. 1054-1088., accepted on January 06, 2022. DOI:10.1093/jssam/smac002
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The reliability of adult self-reported height: The role of interviewers
Olbrich, L., Kosyakova, Y. & Sakshaug, J. (2022): The reliability of adult self-reported height: The role of interviewers. In: Economics and Human Biology, Vol. 45, p. 1-14. DOI:10.1016/j.ehb.2022.101118
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How to Catch a Falsifier: Comparison of Statistical Detection Methods for Interviewer Falsification
Schwanhäuser, S., Sakshaug, J. & Kosyakova, Y. (2022): How to Catch a Falsifier: Comparison of Statistical Detection Methods for Interviewer Falsification. In: Public opinion quarterly, Vol. 86, No. 1, p. 51-81. DOI:10.1093/poq/nfab066
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Introducing Web in a mixed-mode establishment survey: Effects on nonresponse
Gleiser, P., Sakshaug, J., Volkert, M., Ellguth, P., Kohaut, S. & Möller, I. (2022): Introducing Web in a mixed-mode establishment survey: Effects on nonresponse. In: Journal of the Royal Statistical Society. Series A, Statistics in Society, Vol. 185, No. 3, p. 891-915. DOI:10.1111/rssa.12809
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Occupation Coding During the Interview in a Web-First Sequential Mixed-Mode Survey
Peycheva, D., Sakshaug, J. & Calderwood, L. (2021): Occupation Coding During the Interview in a Web-First Sequential Mixed-Mode Survey. In: Journal of Official Statistics, Vol. 37, No. 4, p. 981-1007., accepted on March 17, 2021. DOI:10.2478/jos-2021-0042
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Evaluating the Utility of Linked Administrative Data for Nonresponse Bias Adjustment in a Piggyback Longitudinal Survey
Büttner, T., Sakshaug, J. & Vicari, B. (2021): Evaluating the Utility of Linked Administrative Data for Nonresponse Bias Adjustment in a Piggyback Longitudinal Survey. In: Journal of Official Statistics, Vol. 37, No. 4, p. 837-864. DOI:10.2478/jos-2021-0037
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Trends in Establishment Survey Nonresponse Rates and Nonresponse Bias: Evidence from the 2001-2017 IAB Establishment Panel
König, C., Sakshaug, J., Stegmaier, J. & Kohaut, S. (2021): Trends in Establishment Survey Nonresponse Rates and Nonresponse Bias: Evidence from the 2001-2017 IAB Establishment Panel. In: Journal of Official Statistics, Vol. 37, No. 4, p. 931-953. DOI:10.2478/jos-2021-0040
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Understanding the Patterns of Mode Switching in Longitudinal Studies
Cernat, A. & Sakshaug, J. (2021): Understanding the Patterns of Mode Switching in Longitudinal Studies. In: Survey research methods, Vol. 15, No. 3, p. 281-298., accepted on July 16, 2021. DOI:10.18148/srm/2021.v15i3.7669
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Differences in beliefs about COVID-19 by gun ownership: a cross-sectional survey of Texas adults
Johnson, R., Crifasi, C., Anderson Goodell, E., Wiśniowski, A., Sakshaug, J., Thrul, J. & Owens, M. (2021): Differences in beliefs about COVID-19 by gun ownership: a cross-sectional survey of Texas adults. In: BMJ open, Vol. 11, No. 11, accepted on September 29, 2021. DOI:10.1136/bmjopen-2020-048094
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Respondent Understanding of Data Linkage Consent
Sakshaug, J., Schmucker, A., Kreuter, F., Couper, M. & Holtmann, L. (2021): Respondent Understanding of Data Linkage Consent. In: Survey Methods: Insights from the Field, p. 1-15., accepted on September 27, 2021. DOI:10.13094/SMIF-2021-00008
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More Clarification, Less Item Nonresponse in Establishment Surveys? A Split-Ballot Experiment
Küfner, B., Zins, S. & Sakshaug, J. (2021): More Clarification, Less Item Nonresponse in Establishment Surveys? A Split-Ballot Experiment. In: Survey research methods, Vol. 15, No. 2, p. 195-206., accepted on May 28, 2021. DOI:10.18148/srm/2021.v15i2.7809
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“My next question is, could I have some blood?”
Cernat, A. & Sakshaug, J. (2021): “My next question is, could I have some blood?”. In: Significance, Vol. 18, No. 4, p. 8-9. DOI:10.1111/1740-9713.01543
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Measurement Error in Longitudinal Data
Cernat, A. & Sakshaug, J. (eds.) (2021): Measurement Error in Longitudinal Data. New York, NY: Oxford University Press, 464 p.
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Contact Modes and Participation in App-Based Smartphone Surveys: Evidence From a Large-Scale Experiment
Lawes, M., Hetschko, C., Sakshaug, J. & Grießemer, S. (2022): Contact Modes and Participation in App-Based Smartphone Surveys: Evidence From a Large-Scale Experiment. In: Social science computer review, Vol. 40, No. 5, p. 1076-1092., accepted on January 18, 2021. DOI:10.1177/0894439321993832
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Interviewer Effects in Biosocial Survey Measurements
Cernat, A. & Sakshaug, J. (2021): Interviewer Effects in Biosocial Survey Measurements. In: Field Methods, Vol. 33, No. 3, p. 236-252., accepted on July 21, 2020. DOI:10.1177/1525822X21997231
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Positive Learning or Deviant Interviewing? Mechanisms of Experience on Interviewer Behavior
Kosyakova, Y., Olbrich, L., Sakshaug, J. & Schwanhäuser, S. (2022): Positive Learning or Deviant Interviewing? Mechanisms of Experience on Interviewer Behavior. In: Journal of survey statistics and methodology, Vol. 10, No. 2, p. 249-275. DOI:10.1093/jssam/smab003
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Interviewerkontrolle in der 4. Welle der IAB-BAMF-SOEP-Befragung von Geflüchteten, Stichproben M3-M5
Olbrich, L., Kosyakova, Y., Sakshaug, J. & Schwanhäuser, S. (2020): Interviewerkontrolle in der 4. Welle der IAB-BAMF-SOEP-Befragung von Geflüchteten, Stichproben M3-M5. (SOEP Survey Papers. Series C 901), Berlin, 3 p.
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Nurse Effects on Non-Response in Survey-Based Biomeasures
Cernat, A., Sakshaug, J., Chandola, T., Nazroo, J. & Shlomo, N. (2021): Nurse Effects on Non-Response in Survey-Based Biomeasures. In: International Journal of Social Research Methodology, Vol. 24, No. 4, p. 487-499., accepted on September 30, 2020. DOI:10.1080/13645579.2020.1832737
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Linking Surveys with Big Data
Sakshaug, J. (2020): Linking Surveys with Big Data. Issues of Consent. In: B. Klumpe, J. Schröder & M. Zwick (Hrsg.) (2020): Qualität bei zusammengeführten Daten - Befragungsdaten, Administrative Daten, neue digitale Daten: Miteinander besser?, Wiesbaden, Springer VS p. 163-173, accepted on April 14, 2020. DOI:10.1007/978-3-658-31009-7_12
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Data linkage
Antoni, M. & Sakshaug, J. (2020): Data linkage. In: P. A. Atkinson, A. Cernat, S. Delamont, J. Sakshaug & R. A. Williams (Eds.) (2020): SAGE Research Methods foundations, p. 1-18. DOI:10.4135/9781526421036931838
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Business Data Collection Methodology: Current State and Future Outlook
Bavdaž, M., Snijkers, G., Sakshaug, J., Brand, T., Haraldsen, G., Kurban, B., Saraiva, P. & Willimack, D. (2020): Business Data Collection Methodology: Current State and Future Outlook. In: Statistical Journal of the IAOS, Vol. 36, No. 3, p. 741-756., accepted on June 08, 2020. DOI:10.3233/SJI-200623
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The Impact of Nurse Continuity on Biosocial Survey Participation
Cernat, A. & Sakshaug, J. (2020): The Impact of Nurse Continuity on Biosocial Survey Participation. In: Survey Methods: Insights from the Field, p. 1-14., accepted on July 07, 2020. DOI:10.13094/SMIF-2020-00010
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Impacts of the COVID-19 Pandemic on Labor Market Surveys at the German Institute for Employment Research
Sakshaug, J., Beste, J., Coban, M., Fendel, T., Haas, G., Hülle, S., Kosyakova, Y., König, C., Kreuter, F., Küfner, B., Müller, B., Osiander, C., Schwanhäuser, S., Stephan, G., Vallizadeh, E., Volkert, M., Wenzig, C., Westermeier, C., Zabel, C. & Zins, S. (2020): Impacts of the COVID-19 Pandemic on Labor Market Surveys at the German Institute for Employment Research. In: Survey research methods, Vol. 14, No. 2, p. 229-233. DOI:10.18148/srm/2020.v14i2.7743
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Statistical identification of fraudulent interviews in surveys
Schwanhäuser, S., Sakshaug, J., Kosyakova, Y. & Kreuter, F. (2020): Statistical identification of fraudulent interviews in surveys. Improving interviewer controls. In: K. Olson, J. D. Smyth, J. Dykema, A. Holbrook, F. Kreuter & B. T. West (Eds.) (2020): Interviewer effects from a total survey error perspective, o. Sz.
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Understanding ‘Don't know’ answers to survey questions
Purdam, K., Sakshaug, J., Bourne, M. & Bayliss, D. (2024): Understanding ‘Don't know’ answers to survey questions. An international comparative analysis using interview paradata. In: Innovation: The European Journal of Social Science Research, Vol. 37, No. 2, p. 219-241., accepted on April 03, 2020. DOI:10.1080/13511610.2020.1752631
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A data driven approach to understanding and handling non-response in the Next Steps cohort
Silverwood, R., Calderwood, L., Sakshaug, J. & Ploubidis, G. (2020): A data driven approach to understanding and handling non-response in the Next Steps cohort. (CLS Working Paper 2020/05), London, 34 p.
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The impact of mixed modes on multiple types of measurement error
Cernat, A. & Sakshaug, J. (2020): The impact of mixed modes on multiple types of measurement error. In: Survey research methods, Vol. 14, No. 1, p. 79-91. DOI:10.18148/srm/2020.v14i1.7450
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The impact of synthetic data generation on data utility with application to the 1991 UK samples of anonymised records
Taub, J., Elliot, M. & Sakshaug, J. (2020): The impact of synthetic data generation on data utility with application to the 1991 UK samples of anonymised records. In: Transactions on Data Privacy, Vol. 13, No. 1, p. 1-23.
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Nurse effects on measurement error in household biosocial surveys
Cernat, A. & Sakshaug, J. (2020): Nurse effects on measurement error in household biosocial surveys. In: BMC medical research methodology, Vol. 20, p. 1-9. DOI:10.1186/s12874-020-00922-2
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Recent advances in probability-based and nonprobability survey research
Blom, A., Cornesse, C., Sakshaug, J. & Wenz, A. (2020): Recent advances in probability-based and nonprobability survey research. Editorial. In: Journal of survey statistics and methodology, Vol. 8, No. 1, p. 2-3. DOI:10.1093/jssam/smaa002
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Integrating probability and nonprobability samples for survey inference
Wiśniowski, A., Sakshaug, J., Perez Ruiz, D. & Blom, A. (2020): Integrating probability and nonprobability samples for survey inference. In: Journal of survey statistics and methodology, Vol. 8, No. 1, p. 120-147. DOI:10.1093/jssam/smz051
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A review of conceptual approaches and empirical evidence on probability and nonprobability sample survey research
Cornesse, C., Blom, A., Dutwin, D., Krosnick, J., Leeuw, E., Legleye, S., Pasek, J., Phillips, B., Pennay, D., Phillips, B., Sakshaug, J., Struminskaya, B. & Wenz, A. (2020): A review of conceptual approaches and empirical evidence on probability and nonprobability sample survey research. In: Journal of survey statistics and methodology, Vol. 8, No. 1, p. 4-36. DOI:10.1093/jssam/smz041
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Does benefit framing improve record linkage consent rates?
Sakshaug, J., Stegmaier, J., Trappmann, M. & Kreuter, F. (2019): Does benefit framing improve record linkage consent rates? A survey experiment. In: Survey research methods, Vol. 13, No. 3, p. 289-304. DOI:10.18148/srm/2019.v13i3.7391
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What do we know about voters who say "don't know" in election polls?
Purdam, K. & Sakshaug, J. (2019): What do we know about voters who say "don't know" in election polls? In: The Conversation No. 06.12.2019, o.Sz.
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SAGE Research methods foundations: an encyclopedia
Atkinson, P., Delamont, S., Cernat, A., Sakshaug, J. & Williams, R. (eds.) (2019): SAGE Research methods foundations: an encyclopedia. Los Angeles: Sage, getr. p..
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Supplementing small probability samples with nonprobability samples
Sakshaug, J., Wiśniowski, A., Perez-Ruiz, D. & Blom, A. (2019): Supplementing small probability samples with nonprobability samples. A Bayesian approach. In: Journal of official statistics, Vol. 35, No. 3, p. 653-681. DOI:10.2478/jos-2019-0027
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Multivariate small area estimation of multidimensional latent economic wellbeing indicators
Moretti, A., Shlomo, N. & Sakshaug, J. (2020): Multivariate small area estimation of multidimensional latent economic wellbeing indicators. In: International statistical review, Vol. 88, No. 1, p. 1-28. DOI:10.1111/insr.12333
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Measurement error
Cernat, A., Sakshaug, J. & Castillo, J. (2019): Measurement error. Skin colour and the role of the interviewer. In: Significance, Vol. 16, No. 4, p. 10-11., accepted on June 04, 2019. DOI:10.1111/j.1740-9713.2019.01293.x
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The effect of framing and placement on linkage consent
Sakshaug, J., Schmucker, A., Kreuter, F., Couper, M. & Singer, E. (2019): The effect of framing and placement on linkage consent. In: Public opinion quarterly, Vol. 83, No. S1, p. 289-308. DOI:10.1093/poq/nfz018
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Panel survey recruitment with or without interviewers?
Sakshaug, J., Hülle, S., Schmucker, A. & Liebig, S. (2020): Panel survey recruitment with or without interviewers? Implications for nonresponse, panel consent, and total recruitment bias. In: Journal of survey statistics and methodology, Vol. 8, No. 3, p. 540-565. DOI:10.1093/jssam/smz012
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Identification of interviewer falsification in the IAB-BAMF-SOEP Survey of Refugees in Germany
Kosyakova, Y., Olbrich, L., Sakshaug, J. & Schwanhäuser, S. (2019): Identification of interviewer falsification in the IAB-BAMF-SOEP Survey of Refugees in Germany. (FDZ-Methodenreport 02/2019 (en)), Nürnberg, 33 p. DOI:10.5164/IAB.FDZM.1902.en.v1
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Small area estimation of latent economic well-being
Moretti, A., Shlomo, N. & Sakshaug, J. (2021): Small area estimation of latent economic well-being. In: Sociological methods & research, Vol. 50, No. 4, p. 1660-1693. DOI:10.1177/0049124119826160
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The impact of interviewer effects on skin color assessment in a cross-national context
Cernat, A., Sakshaug, J. & Castillo, J. (2019): The impact of interviewer effects on skin color assessment in a cross-national context. In: International Journal of Public Opinion Research, Vol. 31, No. 4, p. 779-793. DOI:10.1093/ijpor/edy030
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Do sequential mixed-mode surveys decrease nonresponse bias, measurement error bias, and total bias?
Sakshaug, J., Cernat, A. & Raghunathan, T. (2019): Do sequential mixed-mode surveys decrease nonresponse bias, measurement error bias, and total bias? An experimental study. In: Journal of survey statistics and methodology, Vol. 7, No. 4, p. 545-571. DOI:10.1093/jssam/smy024
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Statistical matching as a supplement to record linkage
Gessendorfer, J., Beste, J., Drechsler, J. & Sakshaug, J. (2018): Statistical matching as a supplement to record linkage. A valuable method to tackle nonconsent bias? In: Journal of official statistics, Vol. 34, No. 4, p. 909-933., accepted on June 20, 2018. DOI:10.2478/jos-2018-0045
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Parametric bootstrap mean squared error of a small area multivariate EBLUP
Moretti, A., Shlomo, N. & Sakshaug, J. (2020): Parametric bootstrap mean squared error of a small area multivariate EBLUP. In: Communications in statistics - Simulation and computation, Vol. 49, No. 6, p. 1474-1486. DOI:10.1080/03610918.2018.1498889
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Paper, e-mail, or both?
Sakshaug, J., Vicari, B. & Couper, M. (2019): Paper, e-mail, or both? Effects of contact mode on participation in a web survey of establishments. In: Social science computer review, Vol. 37, No. 6, p. 750-765. DOI:10.1177/0894439318805160
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Accounting for complex sampling in survey estimation: A review of current software tools
West, B., Sakshaug, J. & Aurelien, G. (2018): Accounting for complex sampling in survey estimation: A review of current software tools. In: Journal of official statistics, Vol. 34, No. 3, p. 721-752. DOI:10.2478/jos-2018-0034
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Evaluating the utility of indirectly linked federal administrative records for nonresponse bias adjustment
Sakshaug, J. & Antoni, M. (2019): Evaluating the utility of indirectly linked federal administrative records for nonresponse bias adjustment. In: Journal of Survey Statistics and Methodology, Vol. 7, No. 2, p. 227-249. DOI:10.1093/jssam/smy009
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The need to account for complex sampling features when analyzing establishment survey data: an illustration using the 2013 Business Research and Development Innovation Survey (BRDIS)
West, B. & Sakshaug, J. (2018): The need to account for complex sampling features when analyzing establishment survey data: an illustration using the 2013 Business Research and Development Innovation Survey (BRDIS). In: Survey Methods: Insights from the Field No. Januar 2018, p. 1-10. DOI:10.13094/SMIF-2018-00001
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Linking survey data to official government records
Sakshaug, J. (2018): Linking survey data to official government records. In: D. L. Vanette & J. A. Krosnick (Hrsg.) (2018): The Palgrave Handbook of survey research, p. 597-606, accepted on April 10, 2017. DOI:10.1007/978-3-319-54395-6_67
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Methods of linking survey data to official records
Sakshaug, J. (2018): Methods of linking survey data to official records. In: D. L. Vanette & J. A. Krosnick (Hrsg.) (2018): The Palgrave Handbook of survey research, p. 257-261, accepted on April 10, 2017. DOI:10.1007/978-3-319-54395-6_32
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Analytic error as an important component of total survey error
West, B., Sakshaug, J. & Kim, Y. (2017): Analytic error as an important component of total survey error. Results from a meta-analysis. In: P. P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L. E. Lyberg, N. C. Tucker & B. T. West (Hrsg.) (2017): Total Survey Error in Practice, p. 489-510.
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Biases in multilevel analyses caused by cluster-specific fixed-effects imputation
Speidel, M., Drechsler, J. & Sakshaug, J. (2018): Biases in multilevel analyses caused by cluster-specific fixed-effects imputation. In: Behavior research methods, Vol. 50, No. 5, p. 1824-1840. DOI:10.3758/s13428-017-0951-1
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Obtaining record linkage consent from establishments
Sakshaug, J. & Vicari, B. (2018): Obtaining record linkage consent from establishments. The impact of question placement on consent rates and bias. In: Journal of Survey Statistics and Methodology, Vol. 6, No. 1, p. 46-71. DOI:10.1093/jssam/smx009
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Exploring the effects of interviewer- and self-administered survey modes on record linkage consent rates and bias
Sakshaug, J., Hülle, S., Schmucker, A. & Liebig, S. (2017): Exploring the effects of interviewer- and self-administered survey modes on record linkage consent rates and bias. In: Survey research methods, Vol. 11, No. 2, p. 171-188. DOI:10.18148/srm/2017.v11i2.7158
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Following up with nonrespondents via mode switch and shortened questionnaire in an economic survey
Sakshaug, J. & Eckman, S. (2017): Following up with nonrespondents via mode switch and shortened questionnaire in an economic survey. Evaluating nonresponse bias, measurement error bias, and total bias. In: Journal of Survey Statistics and Methodology, Vol. 5, No. 4, p. 454-479. DOI:10.1093/jssam/smw039
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The quality and selectivity of linking federal administrative records to respondents and nonrespondents in a general population survey in Germany
Sakshaug, J., Antoni, M. & Sauckel, R. (2017): The quality and selectivity of linking federal administrative records to respondents and nonrespondents in a general population survey in Germany. In: Survey research methods, Vol. 11, No. 1, p. 63-80. DOI:10.18148/srm/2017.v11i1.6718
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Errors in linking survey and administrative data
Sakshaug, J. & Antoni, M. (2017): Errors in linking survey and administrative data. In: P. P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L. E. Lyberg, N. C. Tucker & B. T. West (Hrsg.) (2017): Total survey error in practice, p. 557-573.
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Are survey nonrespondents willing to provide consent to use administrative records?
Sakshaug, J. & Eckman, S. (2017): Are survey nonrespondents willing to provide consent to use administrative records? Evidence from a nonresponse follow-up survey in Germany. In: Public opinion quarterly, Vol. 81, No. 2, p. 495-522. DOI:10.1093/poq/nfw053
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Evaluating active (opt-in) and passive (opt-out) consent bias in the transfer of federal contact data to a third-party survey agency
Sakshaug, J., Schmucker, A., Kreuter, F., Couper, M. & Singer, E. (2016): Evaluating active (opt-in) and passive (opt-out) consent bias in the transfer of federal contact data to a third-party survey agency. In: Journal of Survey Statistics and Methodology, Vol. 4, No. 3, p. 382-416. DOI:10.1093/jssam/smw020
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A genetic algorithm approach to synthetic data production
Chen, Y., Elliot, M. & Sakshaug, J. (2016): A genetic algorithm approach to synthetic data production. In: Association for Computing Machinery (Hrsg.) (2016): Proceedings of the 1st International Workshop on AI for Privacy and Security, getr. Sz. DOI:10.1145/2970030.2970034
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How big of a problem is analytic error in secondary analyses of survey data?
West, B., Sakshaug, J. & Aurelien, G. (2016): How big of a problem is analytic error in secondary analyses of survey data? In: PLoS one, Vol. 11, No. 6, p. 1-29. DOI:10.1371/journal.pone.0158120
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Definitely, maybe?
Purdam, K., Bourne, M., Sakshaug, J. & Bayliss, D. (2016): Definitely, maybe? 5 million don't knows and the EU Referendum. (Manchester Policy Blogs), 7 p.
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Does the recruitment of offline households increase the sample representativeness of probability-based online panels?
Blom, A., Herzing, J., Cornesse, C., Sakshaug, J., Krieger, U. & Bossert, D. (2017): Does the recruitment of offline households increase the sample representativeness of probability-based online panels? Evidence from the German internet panel. In: Social science computer review, Vol. 35, No. 4, p. 498-520. DOI:10.1177/0894439316651584
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Classifying open-ended reports: Factors affecting the reliability of occupation codes
Conrad, F., Couper, M. & Sakshaug, J. (2016): Classifying open-ended reports: Factors affecting the reliability of occupation codes. In: Journal of official statistics, Vol. 32, No. 1, p. 75-92. DOI:10.1515/jos-2016-0003
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Obtaining record linkage consent
Sakshaug, J., Wolter, S. & Kreuter, F. (2015): Obtaining record linkage consent. Results from a wording experiment in Germany. In: Survey Methods: Insights from the Field No. 01.11.2015, p. 1-12. DOI:10.13094/SMIF-2015-00012
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An evaluation of panel nonresponse and linkage consent bias in a survey of employees in Germany
Sakshaug, J. & Huber, M. (2016): An evaluation of panel nonresponse and linkage consent bias in a survey of employees in Germany. In: Journal of Survey Statistics and Methodology, Vol. 4, No. 1, p. 71-93. DOI:10.1093/jssam/smv034
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The association between medical home readiness, quality, and care of vulnerable patients
Chen, L., Sakshaug, J., Miller, D., Rosland, A. & Hollingsworth, J. (2015): The association between medical home readiness, quality, and care of vulnerable patients. In: The American journal of managed care, Vol. 21, No. 8, p. e480-e486.
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The framing of the record linkage consent question
Kreuter, F., Sakshaug, J. & Tourangeau, R. (2016): The framing of the record linkage consent question. In: International Journal of Public Opinion Research, Vol. 28, No. 1, p. 142-152. DOI:10.1093/ijpor/edv006
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Generating synthetic microdata to estimate small area statistics in the american community survey
Sakshaug, J. & Raghunathan, T. (2014): Generating synthetic microdata to estimate small area statistics in the american community survey. In: Statistics in transition, Vol. 15, No. 3, p. 341-368.
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The collection of biospecimens in health surveys
Sakshaug, J., Ofstedal, M., Guyer, H. & Beebe, T. (2015): The collection of biospecimens in health surveys. In: T. P. Johnson (Hrsg.) (2015): Handbook of health survey methods (Wiley Handbooks in survey methodology, 01), p. 383-419. DOI:10.1002/9781118594629.ch15
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Nonparametric generation of synthetic data for small geographic areas
Sakshaug, J. & Raghunathan, T. (2014): Nonparametric generation of synthetic data for small geographic areas. In: J. Domingo-Ferrer (Hrsg.) (2014): Privacy in statistical databases 2014 : UNESCO Chair in Data Privacy, International Conference, PSD 2014, Ibiza, Spain, September 17-19, 2014. Proceedings (Lecture Notes in Computer Science, 8744), p. 213-231. DOI:10.1007/978-3-319-11257-2_17
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Availability of in-office laboratory services and use of Prostate Specific Antigen Testing
Sakshaug, J., Hollenbeck, B., Wei, J. & Hollingsworth, J. (2014): Availability of in-office laboratory services and use of Prostate Specific Antigen Testing. In: Urology Practice, Vol. 1, No. 3, p. 111-116. DOI:10.1016/j.urpr.2014.04.005
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Identifying diabetics in medicare claims and survey data
Sakshaug, J., Weir, D. & Nicholas, L. (2014): Identifying diabetics in medicare claims and survey data. Implications for health services research. In: BMC health services research, Vol. 14, No. 150, p. 1-6. DOI:10.1186/1472-6963-14-150
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Generating synthetic data to produce public-use microdata for small geographic areas based on complex sample survey data with application to the national health interview survey
Sakshaug, J. & Raghunathan, T. (2014): Generating synthetic data to produce public-use microdata for small geographic areas based on complex sample survey data with application to the national health interview survey. In: Journal of applied statistics, Vol. 41, No. 10, p. 2103-2122. DOI:10.1080/02664763.2014.909778
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The effect of benefit wording on consent to link survey and administrative records in a web survey
Sakshaug, J. & Kreuter, F. (2014): The effect of benefit wording on consent to link survey and administrative records in a web survey. In: Public opinion quarterly, Vol. 78, No. 1, p. 166-176. DOI:10.1093/poq/nfu001
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The 2010 PASS interviewer survey
Kreuter, F., Sakshaug, J. & Trappmann, M. (2014): The 2010 PASS interviewer survey. Collecting data for research into interviewer effects. (FDZ-Methodenreport 02/2014 (en)), Nürnberg, 92 p.
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Important considerations when analyzing health survey data collected using a complex sample design
Sakshaug, J. & West, B. (2014): Important considerations when analyzing health survey data collected using a complex sample design. In: American Journal of Public Health, Vol. 104, No. 1, p. 15-16. DOI:10.2105/AJPH.2013.301515
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In-office imaging capabilities among procedure-based specialty practices
Hollingsworth, J., Sakshaug, J., Zhang, Y. & Hollenbeck, B. (2014): In-office imaging capabilities among procedure-based specialty practices. In: Surgical innovation, Vol. 21, No. 4, p. 403-408. DOI:10.1177/1553350613505715
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Placement, wording, and interviewers: Identifying correlates of consent to link survey and administrative data
Sakshaug, J., Tutz, V. & Kreuter, F. (2013): Placement, wording, and interviewers: Identifying correlates of consent to link survey and administrative data. In: Survey research methods, Vol. 7, No. 2, p. 133-144.
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Using paradata to study response to within-survey requests
Sakshaug, J. (2013): Using paradata to study response to within-survey requests. In: F. Kreuter (Hrsg.) (2013): Improving surveys with paradata : analytic uses of process information, p. 171-190.
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Experiments in obtaining data linkage consent in web surveys
Sakshaug, J. & Kreuter, F. (2013): Experiments in obtaining data linkage consent in web surveys. In: S. A. Europäische Kommission (Hrsg.) (2013): NTTS - Conferences on New Techniques and Technologies for Statistics. Brussels, 5-7 March 2013. Proceedings, p. 1-6.
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Urologists and the patient-centered medical home
Sakshaug, J., Miller, D., Hollenbeck, B., Wei, J. & Hollingsworth, J. (2013): Urologists and the patient-centered medical home. In: The Journal of Urology, Vol. 190, No. 4, p. 1345-1349. DOI:10.1016/j.juro.2013.03.119
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Readiness of primary care practices for medical home certification
Zickafoose, J., Clark, S., Sakshaug, J., Chen, L. & Hollingsworth, J. (2013): Readiness of primary care practices for medical home certification. In: Pediatrics, Vol. 131, No. 3, p. 473-482. DOI:10.1542/peds.2012-2029
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Linking survey and administrative records
Sakshaug, J., Couper, M., Ofstedal, M. & Weir, D. (2012): Linking survey and administrative records. Mechanisms of consent. In: Sociological Methods and Research, Vol. 41, No. 4, p. 535-569. DOI:10.1177/0049124112460381
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Assessing the magnitude of non-consent biases in linked survey and administrative data
Sakshaug, J. & Kreuter, F. (2012): Assessing the magnitude of non-consent biases in linked survey and administrative data. In: Survey research methods, Vol. 6, No. 2, p. 113-122.
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Multiple imputation of household income in the first wave of PASS
Jaenichen, U. & Sakshaug, J. (2012): Multiple imputation of household income in the first wave of PASS. (FDZ-Methodenreport 02/2012 (en)), Nürnberg, 26 p.
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Physician practices and readiness for medical home reforms
Hollingsworth, J., Saint, S., Sakshaug, J., Hayward, R., Zhang, L. & Miller, D. (2012): Physician practices and readiness for medical home reforms. Policy, pitfalls, and possibilities. In: Health Services Research, Vol. 47, No. 1 Part 2, p. 486-508. DOI:10.1111/j.1475-6773.2011.01332.x
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Using paradata and other auxiliary data to examine mode switch nonresponse in a "recruit-and-switch" telephone survey
Sakshaug, J. & Kreuter, F. (2011): Using paradata and other auxiliary data to examine mode switch nonresponse in a "recruit-and-switch" telephone survey. In: Journal of official statistics, Vol. 27, No. 2, p. 339-357.
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Nonresponse error, measurement error, and mode of data collection
Sakshaug, J., Yan, T. & Tourangeau, R. (2010): Nonresponse error, measurement error, and mode of data collection. Tradeoffs in a multi-mode survey of sensitive and non-sensitive items. In: Public opinion quarterly, Vol. 74, No. 5, p. 907-933. DOI:10.1093/poq/nfq057
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Characteristics of physical measurement consent in a population-based survey of older adults
Sakshaug, J., Couper, M. & Ofstedal, M. (2010): Characteristics of physical measurement consent in a population-based survey of older adults. In: Medical care, Vol. 48, No. 1, p. 64-71. DOI:10.1097/MLR.0b013e3181adcbd3
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Capture-Recapture Sampling
Sakshaug, J. (2008): Capture-Recapture Sampling. In: P. J. Lavrakas (Hrsg.) (2008): Encyclopedia of survey research methods, getr. Sz.
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Measuring and controlling for non-consent bias in linked survey and administrative data
Sakshaug, J. (2021): Measuring and controlling for non-consent bias in linked survey and administrative data. In: A. Y. Chun, M. D. Larsen, G. Durrant & J. Reiter (Eds.) (2021): Administrative records for survey methodology, Hoboken, Wiley p. 155-178, accepted on June 17, 2019.
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Investigating the use of nurse paradata in understanding nonresponse to biological data collection
Pashazadeh, F., Cernat, A. & Sakshaug, J. (2020): Investigating the use of nurse paradata in understanding nonresponse to biological data collection. In: K. Olson, J. D. Smyth, J. Dykema, A. Holbrook, F. Kreuter & B. T. West (Eds.) (2020): Interviewer effects from a total survey error perspective, accepted on January 02, 2020.
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Collection of biomeasures in a cross-national setting
Weiss, L., Sakshaug, J. & Börsch-Supan, A. (2018): Collection of biomeasures in a cross-national setting. Experiences in SHARE. In: T. P. Johnson, B.- E. Pennell, I. Stoop & B. Dorer (Hrsg.) (2018): Advances in comparative survey methods : multinational, multiregional and multicultural contexts (3MC), p. 623-642, accepted on March 04, 2018.
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The Effects of Biological Data Collection in Longitudinal Surveys on Subsequent Wave Nonresponse
Pashazadeh, F., Cernat, A. & Sakshaug, J. (2021): The Effects of Biological Data Collection in Longitudinal Surveys on Subsequent Wave Nonresponse. In: P. Lynn (Ed.) (2021): Advances in Longitudinal Survey Methodology, p. 100-121, accepted on January 05, 2020.
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Combining Scientific and Non-scientific Surveys to Improve Estimation and Reduce Costs
Sakshaug, J., Wiśniowski, A., Perez-Ruiz, D. & Blom, A. (2021): Combining Scientific and Non-scientific Surveys to Improve Estimation and Reduce Costs. In: T. Rudas & G. Péli (eds.) (2021): Pathways between social science and computational social science, Springer p. 71-93, accepted on January 13, 2020. DOI:10.1007/978-3-030-54936-7_4
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Estimating the Measurement Effects of Mixed Modes in Longitudinal Studies
Cernat, A. & Sakshaug, J. (2021): Estimating the Measurement Effects of Mixed Modes in Longitudinal Studies. Current Practice and Issues. In: P. Lynn (Ed.) (2021): Advances in Longitudinal Survey Methodology, p. 227-249, accepted on January 02, 2020.
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Producing Official Statistics during the COVID-19 Pandemic
Jones, J., Ryan, L., Lanyon, A., Apostolou, M., Price, T., König, C., Volkert, M., Sakshaug, J., Mead, D., Baird, H., Elliott, D. & McLaren, C. (2023): Producing Official Statistics during the COVID-19 Pandemic. In: G. Snijkers, M. Bavdaž, S. Bender, S. MacFeely, J. Sakshaug, K. J. Thompson & A. v. Delden (Hrsg.) (2023): Advances in Business Statistics, Methods and Data Collection, p. 225-264, accepted on February 04, 2022.