Publications

Messier K.P., Wheeler D.C., Flory A.R., Jones R.R., Nolan B.T., and Ward M.H. (2019).

Modeling groundwater nitrate exposure in private wells of North Carolina for the Agricultural Health Study.

Science of the Total Environment, 655, 512-519.

DOI | PubMed

Cooper M., Pacek L.R., Guy M.C., Barrington-Trimis J.L., Simon P., Stanton C., and Kong G. (2018).

Hookah use among U.S. youth: A systematic review of the literature from 2009-2017.

Nicotine and Tobacco Research nty135.

DOI | PubMed

Cohn A.M., Johnson A.L., Rose S.W., Pearson J.L., Villanti A.C., and Stanton C. (2018).

Population-level patterns and mental health and substance use correlates of alcohol, marijuana, and tobacco use and co-use in US young adults and adults: Results from the Population Assessment of Tobacco and Health.

American Journal on Addictions, 27(6), 491-500.

DOI | PubMed

Tourangeau R., Yan T., Sun H., Hyland A., and Stanton C.A. (2018).

Population Assessment of Tobacco and Health (PATH) reliability and validity study: Selected reliability and validity estimates.

Tobacco Control.

DOI | PubMed

Jones M., Brick J.M., and Piesse A. (2018).

The effects of address coverage enhancement on estimates from a study using an ABS frame.

Proceedings of the Survey Research Methods Section of the American Statistical Association (pp. 1586-1594). Alexandria, VA: American Statistical Association.

Source

Jiao R. and Piesse A. (2018).

An approach to predict final yield among interim cases.

Proceedings of the Government Statistics Section of the American Statistical Association (pp. 2045-2056). Alexandria, VA: American Statistical Association.

Source

Lin T.-H., Flores Cervantes I., Saito S., and Bain R. (2018).

Evaluating nonresponse weighting adjustment for the Population-Based HIV Impact Assessments Surveys: On incorporating survey outcomes.

Proceedings of the Survey Research Methods Section of the American Statistical Association (pp. 2515-2526). Alexandria, VA: American Statistical Association.

Source

Marker D.A., Mardon R., Jenkins F., Campione J., Nooney J., Li J., Saydeh S., Zhang X., Shrestha S., and Rolka D. (2018).

State-level estimation of diabetes and prediabetes prevalence: Combining national and local survey data and clinical data.

Statistics in Medicine, 37(27), 3975-3990.

DOI | PubMed

Sinha R., Ahsan H., Blaser M., Caporaso J.G., Carmical J.R., Chan A.T., Fodor A., Gail M.H., Harris C.C., Helzlsouer K., Huttenhower C., Knight R., Kong H.H., Lai G.Y., Hutchinson D.L., Le Marchand L., Li H., Orlich M.J., Shi J., Truelove A., Verma M., Vogtmann E., White O., Willett W., Zheng W., Mahabir S., and Abnet C. (2018).

Next steps in studying the human microbiome and health in prospective studies, Bethesda, MD, May 16-17, 2017.

Microbiome, 6, 210.

DOI | PubMed

Tipton E. and Olsen R.B. (2018).

A review of statistical methods for generalizing from evaluations of educational interventions.

Educational Researcher, 47(8), 516-524.

DOI

Williams D. and Brick J.M. (2018).

Trends in U.S. face-to-face household survey nonresponse and level of effort.

Journal of Survey Statistics and Methodology, 6(2), 186-211.

DOI

Suzer-Gurtekin T., Valliant R., Heeringa S.G., and de Leeuw E.D. (2018).

Mixed-mode surveys: Design, estimation and adjustment methods.

In T.P. Johnson, B.E. Pennell, I.A.L. Stroop, and B. Dorer (Eds.), Advances in comparative survey methods: Multinational, multiregional, and multicultural contexts (3MC) (pp. 409-430). Hoboken, NJ: John Wiley and Sons, Inc.

Source

Valliant R., Dever J.A., and Kreuter F. (2018).

Practical tools for designing and weighting survey samples, 2nd edition.

New York, NY: Springer.

Source

Valliant R. and Dever J.A. (2018).

Survey weights: A step-by-step guide to calculation.

College Station, TX: Stata Press.

Source

Chen J.K.T., Valliant R., and Elliott M.R. (2018).

Model-assisted calibration of non-probability sample survey data using adaptive LASSO.

Survey Methodology, 44(1), 117-144.

Source (PDF)

Stanton C.A. and Halenar M.J. (2018).

Patterns and correlates of multiple tobacco product use in the United States.

Nicotine and Tobacco Research, 20(suppl. 1), S1-S4.

DOI | PubMed

Brick J.M. (2018).

Sampling to minimize nonresponse bias.

In D.L. Vannette and J.A. Krosnick (Eds.), The Palgrave handbook of survey research (pp. 23-28). Cham, Switzerland: Palgrave Macmillan.

Source

Brick J.M. (2018).

Optimizing response rates.

In D.L. Vannette and J.A. Krosnick (Eds.), The Palgrave handbook of survey research (pp. 383-391). Cham, Switzerland: Palgrave Macmillan.

Source

Maitland A., Tourangeau R., and Sun H. (2018).

Separating science knowledge from religious belief: Two approaches for reducing the effect of identity on survey responses.

Public Opinion Quarterly, 82(1), 34-62.

DOI

Noel V.A., Francis S.E., and Tilley M.A. (2018).

An adapted measure of sibling attachment: Factor structure and internal consistency of the Sibling Attachment Inventory in youth.

Child Psychiatry & Human Development, 49(2), 217-224.

DOI | PubMed

Metcalfe J.D., Riley J.K., McGurk S.R., Hale T.W., Drake R.E., and Bond G.R. (2018).

Comparing predictors of employment in Individual Placement and Support: A longitudinal analysis.

Psychiatry Research, 264, 85-90.

DOI | PubMed

Finster M. and Milanowski A. (2018).

Teacher perceptions of a new performance evaluation system and their influence on practice: A within- and between-level analysis.

Education Policy Analysis Archives, 26(41).

DOI

Yan T., Keusch F., and He L. (2018).

The impact of question and scale characteristics on scale direction effects.

Survey Practice, 11(2).

DOI

Raithel M.A. (2018).

Validating user-submitted data files with Base SAS.

Proceedings of the SAS Global Forum 2018 Conference. Cary, NC: SAS Institute, Inc.

Source (PDF)

Olsen R.B., Bell S.H., and Nichols A. (2018).

Using preferred applicant random assignment (PARA) to reduce randomization bias in randomized trials of discretionary programs.

Journal of Policy Analysis and Management, 37(1), 167-180.

DOI

Ma H., Ogawa T.K., Sminkey T.R., Breidt F.J., Lesser V.M., Opsomer J.D., Foster J.R., and Van Voorhees D.A. (2018).

Pilot surveys to improve monitoring of marine recreational fisheries in Hawaii.

Fisheries Research, 204, 197-208.

DOI

Mardon R., Marker D., Nooney J., Campione J., Jenkins F., Johnson M., Merrill L., Rolka D.B., Saydah S., Geiss L.S., Zhang X., and Shrestha S. (2017).

Novel methods and data sources for surveillance of state-level diabetes and prediabetes prevalence.

Preventing Chronic Disease, 14, 160572.

DOI | PubMed

Elliott M.R. and Valliant R. (2017).

Inference for nonprobability samples.

Statistical Science, 32(2), 249-264.

Source | DOI

Lee S., Suzer-Gurtekin T., Wagner J., and Valliant R. (2017).

Total survey error and respondent driven sampling: Focus on nonresponse and measurement errors in the recruitment process and the network size reports and implications for inferences.

Journal of Official Statistics, 33(2), 335-366.

Source | DOI

Keith D.R., Stanton C., Gaalema D.E., Bunn J.Y., Doogan N.J., Redner R., Kurti A.N., Cepeda-Benito A., Lopez A.A., Morehead A.L., Roberts M.E., and Higgins S.T. (2017).

Disparities in US healthcare provider screening and advice for cessation across chronic medical conditions and tobacco products.

Journal of General Internal Medicine, 32(9), 974-980.

DOI | PubMed

Siegfried Y., Morganstein D., Piesse A., and Lohr S. (2017).

Why independent surveys with the same objective yield different estimates.

Proceedings of the Survey Research Methods Section of the American Statistical Association (pp. 935-952). Alexandria, VA: American Statistical Association.

Source (PDF)

Lin T., Weil N.V., Flores Cervantes I., and Saito S. (2017).

Developing nonresponse weighting adjustments for population-based HIV impact assessments surveys in three African countries.

Proceedings of the Survey Research Methods Section of the American Statistical Association (pp. 965-982). Alexandria, VA: American Statistical Association.

Source (PDF)

Breidt F.J. and Opsomer J.D. (2017).

Model-assisted survey estimation with modern prediction techniques.

Statistical Science, 32(2), 16.

DOI

Riddles J., Burke J., Rivero G., and Rust K.F. (2017).

Adjustments to student weights to account for student nonresponse in the National Assessment of Educational Progress.

Proceedings of the Survey Research Methods Section of the American Statistical Association (pp. 561-570). Alexandria, VA: American Statistical Association.

Source

Zhou C.K., Young D., Yeboah E.D., Coburn S.B., Tettey Y., Biritwum R.B., Adjei A.A., Tay E., Niwa S., Truelove A., Welsh J., Mensah J.E., Hoover R.N., Sesterhenn I.A., Hsing A.W., Srivastava S., and Cook M.B. (2017).

TMPRSS2:ERG gene fusions in prostate cancer of West African men and a meta-analysis of racial differences.

American Journal of Epidemiology, 186(12), 1352-1361.

DOI | PubMed

Conti D.V., Wang K., Sheng X., Bensen J.T., Hazelett D.J., Cook M.B., Ingles S.A., Kittles R.A., Strom S.S., Rybicki B.A., Nemesure B., Isaacs W.B., Stanford J.L., Zheng W., John E.M., Park J.Y., Xu J., Stevens V.L., Berndt S.I., Sanderson M., Huff C.D., Wang Z., Yeboah E.D., Tettey Y., Biritwum R.B., Adjei A.A., Tay E., Truelove A., Niwa S., Sellers T.A., Yamoah K., Murphy A.B., Crawford D.C., Gapstur S.M., Bush W.S., Aldrich M.C., Cussenot O., Petrovics G., Cullen J., Neslund-Dudas C., Stern M.C., Kote-Jarai Z., Govindasami K., Chokkalingam A.P., Hsing A.W., Goodman P.J., Hoffmann T., Drake B.F., Hu J.J., Clark P.E., Van Den Eeden S.K., Blanchet P., Fowke J.H., Casey G., Hennis A.J., Han Y., Lubwama A., Thompson I.M., Leach R., Easton D.F., Schumacher F., Van Den Berg D., Gundell S.M., Stram A., Wan P., Xia L., Pooler L.C., Mohler J.L., Fontham E.T.H., Smith G.J., Taylor J.A., Srivastava S., Eeles R.A., Carpten J., Kibel A.S., Multigner L., Parent M.E., Menegaux F., Cancel-Tassin G., Klein E.A., Brureau L., Stram D.O., Watya S., Chanock S.J., Witte J.S., Blot W.J., Henderson B.E., Haiman C.A., and for the PRACTICAL/ELLIPSE Consortium (2017).

Two novel susceptibility loci for prostate cancer in men of African ancestry.

Journal of the National Cancer Institute, 109(8).

DOI | PubMed

Noar S.M., Cappella J.N., and Price S.M. (2017).

Communication regulatory science: Mapping a new field.

Health Communication.

DOI | PubMed

Gonzales F.A., Willis G.B., Breen N., Yan T., Cronin K.A., Taplin S.H., and Yu M. (2017).

An exploration of changes in the measurement of mammography in the National Health Interview Survey.

Cancer Epidemiology, Biomarkers, and Prevention, 26(11), 1611-1618.

DOI | PubMed

Wang Z., Berndt S.I., Skibola C.F., de Sanjose S., Melbye M., Glimelius B., Bracci P.M., Conde L., Birmann B.M., Brooks-Wilson A.R., Lan Q., Vermeulen R.C., Link B.K., North K.E., Hjalgrim H., Cozen W., Teras L.R., Spinelli J.J., Zhang Y., Purdue M.P., Giles G.G., Ennas M.G., Monnereau A., Albanes D., Lawrence C., Caporaso N.E., Vajdic C.M., Morton L.M., Holly E.A., Tinker L.F., Vineis P., Cerhan J.R., McKay J., Nieters A., Jackson R.D., Chanock S.J., Diver W.R., Weinstein S., Riboli E., Kraft P., Benavente Y., Boffetta P., Clavel J., Cocco P., Fraumeni J.F., Liebow M., Maynadie M., Offit K., Severson R.K., Southey M.C., Zheng T., Ferri G.M., Miligi L., Smedby K.E., Brennan P., Rothman N., Camp N.J., Call T.G., Glenn M., Curtin K., Goldin L.R., Milne R.L., Law P.J., Speedy H.E., Sava G.P., Holroyd A., Joseph V., Sunter N.J., Bea S., Martin-Garcia D., Clot G., Quintela I., Jayne S., Majid A., Dearden C., Hall A.G., Mainou-Fowler T., Jackson G.H., Marr H., Mansouri L., Topka S., Summerfield G., Harris R.J., Pettitt A.R., Allsup D.J., Bailey J.R., Pratt G., Pepper C., Fegan C., Rosenquist R., Carracedo A., Dyer M.J., Catovsky D., Campo E., Allan J.M., Houlston R., and Slager S. (2017).

Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia.

Nature Communications, 8, 14175.

DOI | PubMed

Edwards B., Maitand A., and Connor S. (2017).

Measurement error in survey operations management: Detection, quantification, visualization, and reduction.

In P.P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L.E. Lyberg, N.C. Tucker, and B.T. West (Eds.), Total survey error in practice (pp. 255-277). (Wiley Series in Survey Methodology). Hoboken, NJ: John Wiley & Sons.

Source

Fay R.E. and Riddles M.K. (2017).

One- versus two-step approaches to survey nonresponse adjustments.

Proceedings of the Joint Statistical Meetings. Alexandria, VA: American Statistical Association.

Source

Huang J.C., Sofolahan-Oladeinde Y., Newhouse R.P., Lavallee D.C., and Mullins C.D. (2017).

Early assessment of the 10-step patient engagement framework for patient-centred outcomes research studies: The first three steps.

Family Practice, 34(3), 272-277.

DOI | PubMed

Brooks G.P., Diaz E.A., and Johanson G.A. (2017).

A precision-based and adaptive approach to number of replications for Monte Carlo studies of robustness and power.

General Linear Model Journal, 43(1), 31-49.

Source (PDF)

Tourangeau R., Brick J.M., Lohr S., and Li J. (2017).

Adaptive and responsive survey designs: A review and assessment.

Journal of the Royal Statistical Society, A, 180(1), 203-223.

DOI

Maitland A., Lin A., Cantor D., Jones M., Moser R., Hesse B., Davis T., and Blake K. (2017).

A nonresponse bias analysis of the Health Information National Trends Survey (HINTS).

Journal of Health Communications 1-9.

DOI | PubMed

Umbach D.M., Sandler D.P., Kamel F., Beard J.D., Keller J., Schmidt S., Engel L.S., Richardson D.B., Gammon M.D., Baird C., Allen K.D., and Stanwyck C.L. (2017).

Military service, deployments, and exposures in relation to amyotrophic lateral sclerosis survival.

PLoS One, 12(10), e0185751.

DOI | PubMed

Tourangeau R., Sun H., Conrad F.G., and Couper M.P. (2017).

Examples in open-ended survey questions.

International Journal of Public Opinion Research, 29(4), 690-702.

DOI

Rust K.F., Krawchuk S., and Monseur C. (2017).

Sample design, weighting, and calculation of sampling variance.

In P. Lietz, J.C. Cresswell, K.F. Rust, and R.J. Adams (Eds.), Implementation of large-scale education assessments. New York, NY: Wiley.

DOI

Yan T. (2017).

Using doorstep concerns data to evaluate and correct for nonresponse error in a longitudinal survey.

In P.P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L.E. Lyberg, N.C. Tucker, and B.T. West (Eds.), Total survey error in practice (pp. 413-430). Hoboken, NJ: John Wiley & Sons.

Source

Yount N.D., Sorra J.S., and Campione J.R. (2017).

Questions regarding the authors' conclusions about the lack of change in Hospital Survey on Patient Safety Culture (HSOPS) scores related to reduction of hospital-acquired infections.

BMJ Quality and Safety.

DOI | PubMed

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You’ll be in great company.

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Centers for Disease Control and Prevention

Centers for Medicare & Medicaid Services

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National Science Foundation

Social Security Administration

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U.S. Department of Education

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U.S. Department of Veterans Affairs

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Maryland Cancer Registry

Michigan Department of Health and Human Services

Texas Education Agency

Baltimore Metropolitan Council

Chicago Metropolitan Agency for Planning

DC Public Schools

NYC Mayor’s Office for Economic Opportunity

Organization for Economic Cooperation and Development

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Teach for America

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University of Denver

University of Maryland Baltimore Campus

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Toyota

U.S. Department of Health and Human Services

Substance Abuse and Mental Health Services Administration

The National Institutes of Health

Publications

Publications

Modeling groundwater nitrate exposure in private wells of North Carolina for the Agricultural Health Study.

Hookah use among U.S. youth: A systematic review of the literature from 2009-2017.

Population-level patterns and mental health and substance use correlates of alcohol, marijuana, and tobacco use and co-use in US young adults and adults: Results from the Population Assessment of Tobacco and Health.

Population Assessment of Tobacco and Health (PATH) reliability and validity study: Selected reliability and validity estimates.

The effects of address coverage enhancement on estimates from a study using an ABS frame.

An approach to predict final yield among interim cases.

Evaluating nonresponse weighting adjustment for the Population-Based HIV Impact Assessments Surveys: On incorporating survey outcomes.

State-level estimation of diabetes and prediabetes prevalence: Combining national and local survey data and clinical data.

Next steps in studying the human microbiome and health in prospective studies, Bethesda, MD, May 16-17, 2017.

A review of statistical methods for generalizing from evaluations of educational interventions.

Trends in U.S. face-to-face household survey nonresponse and level of effort.

Mixed-mode surveys: Design, estimation and adjustment methods.

Practical tools for designing and weighting survey samples, 2nd edition.

Survey weights: A step-by-step guide to calculation.

Model-assisted calibration of non-probability sample survey data using adaptive LASSO.

Patterns and correlates of multiple tobacco product use in the United States.

Sampling to minimize nonresponse bias.

Optimizing response rates.

Separating science knowledge from religious belief: Two approaches for reducing the effect of identity on survey responses.

An adapted measure of sibling attachment: Factor structure and internal consistency of the Sibling Attachment Inventory in youth.

Comparing predictors of employment in Individual Placement and Support: A longitudinal analysis.

Teacher perceptions of a new performance evaluation system and their influence on practice: A within- and between-level analysis.

The impact of question and scale characteristics on scale direction effects.

Validating user-submitted data files with Base SAS.

Using preferred applicant random assignment (PARA) to reduce randomization bias in randomized trials of discretionary programs.

Pilot surveys to improve monitoring of marine recreational fisheries in Hawaii.

Novel methods and data sources for surveillance of state-level diabetes and prediabetes prevalence.

Inference for nonprobability samples.

Total survey error and respondent driven sampling: Focus on nonresponse and measurement errors in the recruitment process and the network size reports and implications for inferences.

Disparities in US healthcare provider screening and advice for cessation across chronic medical conditions and tobacco products.

Why independent surveys with the same objective yield different estimates.

Developing nonresponse weighting adjustments for population-based HIV impact assessments surveys in three African countries.

Model-assisted survey estimation with modern prediction techniques.

Adjustments to student weights to account for student nonresponse in the National Assessment of Educational Progress.

TMPRSS2:ERG gene fusions in prostate cancer of West African men and a meta-analysis of racial differences.

Two novel susceptibility loci for prostate cancer in men of African ancestry.

Communication regulatory science: Mapping a new field.

An exploration of changes in the measurement of mammography in the National Health Interview Survey.

Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia.

Measurement error in survey operations management: Detection, quantification, visualization, and reduction.

One- versus two-step approaches to survey nonresponse adjustments.

Early assessment of the 10-step patient engagement framework for patient-centred outcomes research studies: The first three steps.

A precision-based and adaptive approach to number of replications for Monte Carlo studies of robustness and power.

Adaptive and responsive survey designs: A review and assessment.

A nonresponse bias analysis of the Health Information National Trends Survey (HINTS).

Military service, deployments, and exposures in relation to amyotrophic lateral sclerosis survival.

Examples in open-ended survey questions.

Sample design, weighting, and calculation of sampling variance.

Using doorstep concerns data to evaluate and correct for nonresponse error in a longitudinal survey.

Questions regarding the authors' conclusions about the lack of change in Hospital Survey on Patient Safety Culture (HSOPS) scores related to reduction of hospital-acquired infections.

Want to work with us?You’ll be in great company.

Want to work with us?
You’ll be in great company.