Accesso libero

Identifying Outliers in Response Quality Assessment by Using Multivariate Control Charts Based on Kernel Density Estimation

INFORMAZIONI SU QUESTO ARTICOLO

Cita

Ahsan, M., M. Mashuri, H. Kuswanto, D.D. Prastyo, and H. Khusna. 2018. “Multivariate Control Chart Based on PCA Mix for Variable and Attribute Quality Characteristics.” Production & Manufacturing Research 6(1): 364–384. DOI: https://doi.org/10.1080/21693277.2018.1517055.10.1080/21693277.2018.1517055Search in Google Scholar

Bersimis, S., J. Panaretos, and S. Psarakis. 2005. “Multivariate Statistical Process Control Charts and the Problem of Interpretation: A Short Overview and Some Applications in Industry.” In Proceedings of the 7th Hellenic European Conference on Computer Mathematics and Its Applications. Athens, Greece. September 22–24, 2005. Available at: https://arxiv.org/ftp/arxiv/papers/0901/0901.2880.pdf (accessed September 2020).Search in Google Scholar

Billiet, J.B., and M.J. McClendon. 2000. “Modeling Acquiescence in Measurement Models for Two Balanced Sets of Items.” Structural Equation Modeling 7(4): 608–628. DOI: https://doi.org/10.1207/S15328007SEM0704_5.10.1207/S15328007SEM0704_5Search in Google Scholar

Chakraborti, S., S. Human, and M. Graham. 2008. “Phase I Statistical Process Control Charts: An Overview and Some Results.” Quality Engineering 21(1): 52–62. DOI: https://doi.org/10.1080/08982110802445561.10.1080/08982110802445561Search in Google Scholar

Chavent, M., V. Kuentz-Simonet, A. Labenne, and J. Saracco. 2014. “Multivariate Analysis of Mixed Data: The R Package PCAmixdata.” Available at: https://arxiv.org/abs/1411.4911 (accessed September 2020).Search in Google Scholar

Chou, Y.-M., R.L. Mason, and J.C. Young. 2001. “The Control Chart for Individual Observations from a Multivariate Non-Normal Distribution.” Communications in Statistics–Theory and Methods 30(8-9): 1937–1949. DOI: https://doi.org/10.1081/-STA-100105706.Search in Google Scholar

Cleveland, W.S. 1979. “Robust Locally Weighted Regression and Smoothing Scatterplots.” Journal of the American Statistical Association 74(368): 829–836. DOI: http://doi.org/10.1080/01621459.1979.10481038.10.1080/01621459.1979.10481038Search in Google Scholar

Cleveland, W.S., and S.J. Devlin. 1988. “Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting.” Journal of the American Statistical Association 83(403): 596–610. DOI: http://doi.org/10.1080/01621459.1988.10478639.10.1080/01621459.1988.10478639Search in Google Scholar

Corsetti, G., M. Giammatteo, and A. Martini. 2010. “Monitoring Process and Non-sampling Errors Control in PLUS Sample Survey.” In Proceedings of the European Conference on Quality in Official Statistics (Q2010). Helsinki, Finland. May 4–6, 2010. Available at: https://q2010.stat.fi/media/presentations/session24/corsetti_giammatteo_-martini_q2010_v2_paper.pd (accessed September 2020).Search in Google Scholar

Costa, F.S., R.H. Pedroza, D.L. Porto, M.V. Amorim, and K.M. Lima. 2015. “Multivariate Control Charts for Simultaneous Quality Monitoring of Isoniazid and Rifampicin in a Pharmaceutical Formulation Using a Portable Near Infrared Spectrometer.” Journal of the Brazilian Chemical Society 26(1): 64–73. DOI: http://dx.doi.org/10.5935/0103-5053.20140214.10.5935/0103-5053.20140214Search in Google Scholar

Ferrer, A. 2007. “Multivariate Statistical Process Control Based on Principal Component Analysis (MSPC-PCA): Some Reflections and a Case Study in An Autobody Assembly Process.” Quality Engineering 19(4): 311 – 325. DOI: https://doi.org/10.1080/08982110701621304.10.1080/08982110701621304Search in Google Scholar

Groves, R.M., and S.G. Heeringa. 2006. “Responsive Design for Household Surveys: Tools for Actively Controlling Survey Errors and Costs.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 169(3): 439 – 457. DOI: https://doi.org/10.1111/j.1467-985X.2006.00423.x.10.1111/j.1467-985X.2006.00423.xSearch in Google Scholar

Hotelling, H. 1947. “Multivariate Quality Control–illustrated by the Air Testing of Sample Bombsights.” In Techniques of Statistical Analysis, edited by C. Eisenhart, M. Hastay, and W. Wallis, 111–184. New York: McGraw-Hill.Search in Google Scholar

Hubert, M., and M. Debruyne. 2010. “Minimum Covariance Determinant.” Wiley Interdisciplinary Reviews: Computational Statistics 2(1): 36–43. DOI: https://doi.org/10.1002/wics.61.10.1002/wics.61Search in Google Scholar

Hubert, M., M. Debruyne, and P.J. Rousseeuw. 2018. “Minimum Covariance Determinant and Extensions.” Wiley Interdisciplinary Reviews: Computational Statistics 10(3): E1421. DOI: https://doi.org/10.1002/wics.1421.10.1002/wics.1421Search in Google Scholar

Jans, M., R. Sirkis, and D. Morgan. 2013. “Managing Data Quality Indicators With Paradata Based Statistical Quality Control Tools: The Keys to Survey Performance.” In Improving Surveys With Paradata. Analytic Uses of Process Information, Edited by F. Kreuter, 191–229. John Wiley & Sons, Inc.10.1002/9781118596869.ch9Search in Google Scholar

Jin, J., and G. Loosveldt. 2020. “Assessing Response Quality by Using Multivariate Control Charts for Numerical and Categorical Response Quality Indicators.” Journal of Survey Statistics and Methodology. ISSN: 2325-0984. DOI: https://doi.org/10.1093/jssam/smaa012.10.1093/jssam/smaa012Search in Google Scholar

Jin, J., C. Vandenplas, and G. Loosveldt. 2019. “The Evaluation of Statistical Process Control Methods to Monitor Interview Duration During Survey Data Collection.” Sage Open 9(2). DOI: https://doi.org/10.1177/2158244019854652.10.1177/2158244019854652Search in Google Scholar

Kini, K.R., and M. Madakyaru. 2016. “Multivariate Statistical Based Process Monitoring Using Principal Component Analysis: An Application to Chemical Reactor.” International Journal of Control Theory and Applications 9(39): 303–311.Search in Google Scholar

Kreuter, F., M. Couper, and L. Lyberg. 2010. “The Use of Paradata to Monitor and Manage Survey Data Collection.” In Proceedings of the Joint Statistical Meetings, 282–296. Vanouver, Canada. August 2–4, 2010. Available at: http://sampieuchair.ec.unipi.it/wp-content/uploads/2018/10/Couper-etal.pdf (accessed September 2020).Search in Google Scholar

Krosnick, J.A. 1991. “Response Strategies for Coping With the Cognitive Demands of Attitude Measures in Surveys.” Applied Cognitive Psychology 5(3): 213–236. DOI: https://doi.org/10.1002/acp.2350050305.10.1002/acp.2350050305Search in Google Scholar

Loosveldt, G., and K. Beullens. 2017. “Interviewer Effects on Non-differentiation and Straightlining in the European Social Survey.” Journal of Official Statistics 33(2): 409–426. DOI: https://doi.org/10.1515/jos-2017-0020.10.1515/jos-2017-0020Search in Google Scholar

MacCarthy, B., and T. Wasusri. 2002. “A Review of Non-standard Applications of Statistical Process Control (SPC) Charts.” International Journal of Quality & Reliability Management 19(3): 295 – 320. DOI: http://doi.org/10.1108/02656710210415695.10.1108/02656710210415695Search in Google Scholar

MacGregor, J.F., and T. Kourti. 1995. “Statistical Process Control of Multivariate Processes.” Control Engineering Practice 3(3): 403–414. DOI: https://doi.org/10.1016/0967-0661(95)00014-L.10.1016/0967-0661(95)00014-LSearch in Google Scholar

Mason, R., and J. Young. 2002. Multivariate Statistical Process Control With Industrial Applications. ASA-SIAM Series on Statistics and Applied Probability. Society for Industrial/Applied Mathematics. DOI: https://doi.org/10.1137/1.9780898718461.10.1137/1.9780898718461Search in Google Scholar

Montgomery, D.C. 2009. Introduction to Statistical Quality Control. New York: John Wiley & Sons.Search in Google Scholar

Peng, D., and K. Feld. 2011. “Quality Control in Telephone Survey Interviewer Monitoring.” Survey Practice 4(2). DOI: https://doi.org/10.29115/SP-2011-0011.10.29115/SP-2011-0011Search in Google Scholar

Phaladiganon, P., S.B. Kim, V.C. Chen, J.-G. Baek, and S.-K. Park. 2011. “Bootstrap-based T2 Multivariate Control Charts.” Communications in Statistics–Simulation and Computation 40(5): 645–662. DOI: https://doi.org/10.1080/03610918.2010.549989.10.1080/03610918.2010.549989Search in Google Scholar

Polansky, A.M., and E.R. Baker. 2000. “Multistage Plug–in Bandwidth Selection for Kernel Distribution Function Estimates.” Journal of Statistical Computation and Simulation 65(1-4): 63–80. DOI: https://doi.org/10.1080/00949650008811990.10.1080/00949650008811990Search in Google Scholar

Rammstedt, B., D. Danner, and M. Bosnjak. 2017. “Acquiescence Response Styles: a Multilevel Model Explaining Individual-level and Country-level differences.” Personality and Individual Differences 107:190–194. DOI: https://doi.org/10.1016/j.-paid.2016.11.038.Search in Google Scholar

Rocke, D.M., and D.L. Woodruff. 1996. “Identification of Outliers in Multivariate Data.” Journal of the American Statistical Association 91(435): 1047 – 1061. DOI: https://doi.org/10.2307/2291724.10.1080/01621459.1996.10476975Search in Google Scholar

Rousseeuw, P.J. 1984. “Least Median of Squares Regression.” Journal of the American Statistical Association 79(388): 871–880. DOI: https://doi.org/10.1080/01621459.1984.10477105.10.1080/01621459.1984.10477105Search in Google Scholar

Rousseeuw, P.J. 1985. “Multivariate Estimation With High Breakdown Point.” In Mathematical Statistics and Applications: Proceedings of the Fourth Pannonian Symposium on Mathematical Statistics and Probability, 283–297. Bad Tatzmannsdorf, Austria. September 4–10, 1985. Available at: https://wis.kuleuven.be/stat/robust/papers/publications-1985/rousseeuw-multivAriateestimationhighbreakdown-1985.pdf (accessed September 2020).10.1007/978-94-009-5438-0_20Search in Google Scholar

Rousseeuw, P.J., and K.V. Driessen. 1999. “A Fast Algorithm for the Minimum Covariance Determinant Estimator.” Technometrics 41(3): 212–223. DOI: https://doi.org/10.1080/00401706.1999.10485670.10.1080/00401706.1999.10485670Search in Google Scholar

Scherkenbach, W.W. 1986. The Deming Route to Quality and Productivity: Road Maps and Roadblocks. Washington, DC: CEE Press.Search in Google Scholar

Schouten, B., A. Peytchev, and J. Wagner. 2017. Adaptive Survey Design. Boca Raton, FL: Chapman & Hall/CRC.10.1201/9781315153964Search in Google Scholar

Shewhart, W.A. 1931. Economic Control of Quality of Manufactured Product. London: Macmillan.Search in Google Scholar

Simon, H.A. 1956. “Rational Choice and the Structure of the Environment.” Psychological Review 63(2): 129–138. DOI: https://doi.org/10.1037/h0042769.10.1037/h004276913310708Search in Google Scholar

Sirkis, R., M. Jans, J. Dahlhamer, R. Gindi, and B. Duffey. 2011. “Using Statistical Process Control to Understand Variation in Computer-assisted Personal Interviewing Data.” In Proceedings of the Survey Research Methods Section, 477–489. Miami Beach, FL. July 30 – August 4, 2011. Available at: http://www.asasrms.org/Proceedings/y2011/Files/300484_65051.pdf (accessed September 2020).Search in Google Scholar

Wagner, J.R. 2008. “Adaptive Survey Design to Reduce Nonresponse Bias.” PhD Thesis, University of Michigan. Available at: https://deepblue.lib.umich.edu/bitstream/handle/2027.42/60831/jameswag_1.pdf?sequence=1&isAllowed=y (accessed January 2021).Search in Google Scholar

Yan, T., R. Tourangeau, and Z. Arens. 2004. “When Less is More: Are Reluctant Respondents Poor Reporters?” In Proceedings of the Survey Research Methods Section. Toronto, Canada. August 8-12, 2004. Available at: http://www.asasrms.org/Proceedings/y2004/files/Jsm2004-000169.pdf. (accessed September 2020).Search in Google Scholar

eISSN:
2001-7367
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Mathematics, Probability and Statistics