Skinner, Chris J.

Number of items: 88.
Article
  • Skinner, Chris, Lawson, Nuanpan (2025). Nonresponse adjustment using auxiliary variables subject themselves to missing data. WSEAS Transactions on Systems, 24, 106 - 111. https://doi.org/10.37394/23202.2025.24.12 picture_as_pdf
  • Jamil, Haziq, Moustaki, Irini, Skinner, Chris J. (2025). Pairwise likelihood estimation and limited-information goodness-of-fit test statistics for binary factor analysis models under complex survey sampling. British Journal of Mathematical and Statistical Psychology, 78(1), 258 - 285. https://doi.org/10.1111/bmsp.12358 picture_as_pdf
  • Shlomo, Natalie, Skinner, Chris (2022). Measuring risk of re-identification in microdata: state-of-the art and new directions. Journal of the Royal Statistical Society. Series A: Statistics in Society, 185(4), 1644 - 1662. https://doi.org/10.1111/rssa.12902 picture_as_pdf
  • Burchardt, Tania, Steele, Fiona, Grundy, Emily, Karagiannaki, Eleni, Kuha, Jouni, Moustaki, Irini, Skinner, Chris, Zhang, Nina, Zhang, Siliang (2021). Welfare within families beyond households: intergenerational exchanges of practical and financial support in the UK. LSE Public Policy Review, 2(1). https://doi.org/10.31389/lseppr.41 picture_as_pdf
  • Skinner, Chris J., Steele, Fiona (2020). Estimation of dyadic characteristics of family networks using sample survey data. Annals of Applied Statistics, 14(2), 706 - 726. https://doi.org/10.1214/19-AOAS1308 picture_as_pdf
  • Lee, D, Kim, J K, Skinner, Chris J. (2019). Within-cluster resampling for multilevel models under informative cluster size. Biometrika, 106(4), 965-972. https://doi.org/10.1093/biomet/asz035 picture_as_pdf
  • Skinner, Chris J. (2018). Analysis of categorical data for complex surveys. International Statistical Review, https://doi.org/10.1111/insr.12285
  • Rinott, Yosef, O’Keefe, Christine M., Shlomo, Natalie, Skinner, Chris J. (2018). Confidentiality and differential privacy in the dissemination of frequency tables. Statistical Science, 33(3), 358-385. https://doi.org/10.1214/17-STS641
  • Kuha, Jouni, Butt, Sarah, Katsikatsou, Myrsini, Skinner, Chris J. (2018). The effect of probing "don't know" responses on measurement quality and nonresponse in surveys. Journal of the American Statistical Association, 113(521), 26 - 40. https://doi.org/10.1080/01621459.2017.1323640
  • Skinner, Chris J. (2017). Comments on the Rao and Fuller (2017) paper. Survey Methodology, 43, 179-181.
  • Kuha, Jouni, Butt, Sarah, Katsikatsou, Myrsini, Skinner, Chris J. (2017). Probing of "don't know'' responses in surveys. MethodsNews, 3(2017), p. 6.
  • Lawson, Nuanpan, Skinner, Chris (2017). Estimation of a cluster-level regression model under nonresponse within clusters. Metron, 75(3), 319-331. https://doi.org/10.1007/s40300-017-0120-4
  • Skinner, Chris J., Wakefield, Jon (2017). Introduction to the design and analysis of complex survey data. Statistical Science, 32(2), 165-175. https://doi.org/10.1214/17-STS614
  • Gaboardi, Marco, Skinner, Chris J. (2017). Special issue on the theory and practice of differential privacy. Journal of Privacy and Confidentiality, 7(2).
  • Berg, Emily, Kim, J. K., Skinner, Chris (2016). Imputation under informative sampling. Journal of Survey Statistics and Methodology, 4(4), 436-462. https://doi.org/10.1093/jssam/smw032
  • Da Silva, Damião Nóbrega, Skinner, Chris J., Kim, Jae Kwang (2016). Using binary paradata to correct for measurement error in survey data analysis. Journal of the American Statistical Association, 111(514), 526 - 537. https://doi.org/10.1080/01621459.2015.1130632
  • Skinner, C. J. (2015). Cross-classified sampling: some estimation theory. Statistics and Probability Letters, 104, 163-168. https://doi.org/10.1016/j.spl.2015.06.001
  • Goldstein, Harvey, Lynn, Peter, Muniz-Terrera, Graciela, Hardy, Rebecca, O’Muircheartaigh, Colm, Skinner, Chris J., Lehtonen, Risto (2015). Population sampling in longitudinal surveys. Longitudinal and Life Course Studies, 6(4), 447-475. https://doi.org/10.14301/llcs.v6i4.345 picture_as_pdf
  • Da Silva, Damião Nóbrega, Skinner, Chris J. (2014). The use of accuracy indicators to correct for survey measurement error. Journal of the Royal Statistical Society. Series C: Applied Statistics, 63(2), 303-319. https://doi.org/10.1111/rssc.12022
  • Kim, Jae Kwang, Skinner, Chris J. (2013). Weighting in survey analysis under informative sampling. Biometrika, 100(2), 385-398. https://doi.org/10.1093/biomet/ass085
  • Skinner, Chris, Mason, Ben (2012). Weighting in the regression analysis of survey data with a cross-national application. Canadian Journal of Statistics, 40(4), 697-711. https://doi.org/10.1002/cjs.11155
  • Skinner, Chris J., Shlomo, N. (2012). Estimating frequencies of frequencies in finite populations. Statistics and Probability Letters, 82(12), 2206-2212. https://doi.org/10.1016/j.spl.2012.07.023
  • Skinner, Chris J. (2012). Rejoinder. International Statistical Review, 80(3), 379-381. https://doi.org/10.1111/j.1751-5823.2012.00192.x
  • Skinner, Chris J. (2012). Statistical disclosure risk: separating potential and harm. International Statistical Review, 80(3), 349-368. https://doi.org/10.1111/j.1751-5823.2012.00194.x
  • Shlomo, Natalie, Skinner, Chris J., Schouten, Barry (2012). Estimation of an indicator of the representativeness of survey response. Journal of Statistical Planning and Inference, 142(1), 201-211. https://doi.org/10.1016/j.jspi.2011.07.008
  • Micklewright, John, Schnepf, Sylke, Skinner, Chris J. (2012). Non-response biases in surveys of schoolchildren: the case of the English Programme for International Student Assessment (PISA) samples. Journal of the Royal Statistical Society. Series A: Statistics in Society, 175(4), 915-338. https://doi.org/10.1111/j.1467-985X.2012.01036.x
  • Sholmo, Natalie, Skinner, Chris J. (2012). Privacy protection from sampling and perturbation in survey microdata. Journal of Privacy and Confidentiality, 4(1), 155-169.
  • Schouten, Barry, Shlomo, Natalie, Skinner, Chris J. (2011). Indicators for monitoring and improving representativeness of response. Journal of Official Statistics, 27(2), 231-253.
  • Skinner, Chris J. (2011). Book review: 'advances in sampling theory - ratio method of estimation’ by Cingi, H. and Kadilar, C. Journal of the American Statistical Association, 106(493), 375-382. https://doi.org/10.1198/jasa.2011.br1103.
  • Skinner, Chris J., D'Arrigo, Julia (2011). Inverse probability weighting for clustered nonresponse. Biometrika, 98(4), 953-966. https://doi.org/10.1093/biomet/asr058
  • D'Arrigo, Julia, Skinner, Chris J. (2010). Linearization variance estimation for generalized raking estimators in the presence of nonresponse. Survey Methodology, 36(2), 181-192.
  • Shlomo, Natalie, Skinner, Chris J. (2010). Assessing the protection provided by misclassification-based disclosure limitation methods for survey microdata. Annals of Applied Statistics, 4(3), 1291-1310. https://doi.org/10.1214/09-AOAS317
  • Skinner, Chris J., Vallet, L.-A. (2010). Fitting log-linear models to contingency tables from surveys with complex sampling designs: an investigation of the Clogg-Eliason approach. Sociological Methods and Research, 39(1), 83-108. https://doi.org/10.1177/0049124110366239
  • Young, Caroline, Martin, David, Skinner, Chris J. (2009). Geographically intelligent disclosure control for flexible aggregation of census data. International Journal of Geographical Information Science, 23(4), 457-482. https://doi.org/10.1080/13658810801949835
  • Matei, Alina, Skinner, Chris J. (2009). Optimal sample coordination using controlled selection. Journal of Statistical Planning and Inference, 139(9), 3112-3121. https://doi.org/10.1016/j.jspi.2009.02.012
  • Vieira, Marcel D.T., Skinner, Chris J. (2008). Estimating models for panel survey data under complex sampling. Journal of Official Statistics, 24(3), 343-364.
  • Skinner, Chris J., Shlomo, Natalie (2008). Assessing identification risk in survey microdata using log-linear models. Journal of the American Statistical Association, 103(483), 989-1001. https://doi.org/10.1198/016214507000001328
  • Ekholm, Anders, Skinner, Chris J. (2008). The Muscatine children’s obesity data reanalysed using pattern mixture models. Journal of the Royal Statistical Society. Series C: Applied Statistics, 47(2), 251-263. https://doi.org/10.1111/1467-9876.00110
  • Skinner, Chris J. (2007). Discussion of J.F.Bjørnstad, ‘Non-Bayesian multiple imputation’. Journal of Official Statistics, 23(4), 463-465.
  • Skinner, Chris J., de Toledo Vieira, Marcel (2007). Variance estimation in the analysis of clustered longitudinal survey data. Survey Methodology, 33(1), 3-12.
  • Ali Ghazali, Syed Shakir, Skinner, Chris J., Tahir, M. H. (2007). Three-way stratification sampling design when one of the stratifying variables is time. Australian and New Zealand Journal of Statistics, 49(4), 385-395. https://doi.org/10.1111/j.1467-842X.2007.00489.x
  • Skinner, Chris J. (2007). The probability of identification: applying ideas from forensic statistics to disclosure risk assessment. Journal of the Royal Statistical Society. Series A: Statistics in Society, 170(1), 195-212. https://doi.org/10.1111/j.1467-985X.2006.00457.x
  • Elamir, Elsayed A.H., Skinner, Chris J. (2006). Record level measures of disclosure risk for survey microdata. Journal of Official Statistics, 22(3), 525-539.
  • Durrant, Gabriele B., Skinner, Chris J. (2006). Using data augmentation to correct for non-ignorable non-response when surrogate data are available: an application to the distribution of hourly pay. Journal of the Royal Statistical Society. Series A: Statistics in Society, 169(3), 605-623. https://doi.org/10.1111/j.1467-985X.2006.00398.x
  • Durrant, Gabriele B., Skinner, Chris J. (2006). Using missing data methods to correct for measurement error in a distribution function. Survey Methodology, 32(1), 25-36.
  • Skinner, Chris J. (2005). Contribution to discussion of J. Copas and S. Eguchi, ‘local model uncertainty and incomplete-data bias’. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 67(4), p. 500. https://doi.org/10.1111/j.1467-9868.2005.00512.x
  • Berger, Yves G., Skinner, Chris J. (2005). A jackknife variance estimator for unequal probability sampling. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 67(1), 79-89. https://doi.org/10.1111/j.1467-9868.2005.00489.x
  • Skinner, Chris J. (2004). Comment on: A. Demnati and J.N.K. Rao, 'linearization variance estimators for model parameters from complex survey data'. Survey Methodology, 30(1), 17-18.
  • Skinner, Chris J., Carter, Randy (2003). Estimation of a measure of disclosure risk for survey microdata under unequal probability sampling. Survey Methodology, 29(2), 177-180.
  • Berger, Yves G., Skinner, Chris J. (2003). Variance estimation for a low income proportion. Journal of the Royal Statistical Society. Series C: Applied Statistics, 52(4), 457-468. https://doi.org/10.1111/1467-9876.00417
  • Skinner, Chris J. (2002). Discussion. Journal of Official Statistics, 18(2), 155-156.
  • Skinner, Chris J. (2002). Jackknife variance estimation for multivariate statistics under hot-deck imputation from common donors. Journal of Statistical Planning and Inference, 102(1), 149-167. https://doi.org/10.1016/S0378-3758(01)00185-9
  • Skinner, Chris J., Elliot, M. J. (2002). A measure of disclosure risk for microdata. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 64(4), 855-867. https://doi.org/10.1111/1467-9868.00365
  • Skinner, Chris J., Stuttard, Nigel, Beissel-Durrant, Gabriele, Jenkins, James (2002). The measurement of low pay in the UK labour force survey. Oxford Bulletin of Economics and Statistics, 64(supple), 653-676. https://doi.org/10.1111/1468-0084.64.s.5
  • Smith, P. W. F., Skinner, Chris J., Clarke, P. S. (1999). Allowing for non-ignorable non-response in the analysis of voting intention data. Journal of the Royal Statistical Society. Series C: Applied Statistics, 48(4), 563-577. https://doi.org/10.1111/1467-9876.00172
  • Skinner, Chris J. (1999). Calibration weighting and non-sampling errors. Research in Official Statistics, 2, 33-43.
  • Romaniuk, H., Skinner, Chris J., Cooper, P. J. (1999). Modelling consumers' use of products. Journal of the Royal Statistical Society. Series A: Statistics in Society, 162(3), 407-421. https://doi.org/10.1111/1467-985X.00144
  • Skinner, Chris J., Humphreys, K. (1999). Weibull regression for lifetimes measured with error. Lifetime Data Analysis, 5(1), 23-37. https://doi.org/10.1023/A:1009674915476
  • Holmes, D. J., Skinner, Chris J. (1998). Estimating the re-identification risk per record in microdata. Journal of Official Statistics, 14(4), 361-372.
  • Skinner, Chris J. (1998). Logistic modelling of longitudinal survey data with measurement error. Statistica Sinica, 8(4), 1045-1058.
  • Rao, J. N. K., Scott, A. J., Skinner, Chris J. (1998). Quasi-score tests with survey data. Statistica Sinica, 8(4), 1059-1070.
  • Elliot, M. J., Skinner, Chris J., Dale, A. (1998). Special uniques, random uniques and sticky populations: some counterintuitive effects of geographical detail on disclosure risk. Research in Official Statistics, 1, 53-67.
  • Pfeffermann, Danny, Skinner, Chris J., Holmes, D. J., Goldstein, H., Rasbash, J. (1998). Weighting for unequal selection probabilities in multilevel models. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 60(1), 23-40. https://doi.org/10.1111/1467-9868.00106
  • Pfeffermann, Danny, Skinner, Chris J., Humphreys, Keith (1998). The estimation of gross flows in the presence of measurement error using auxiliary variables. Journal of the Royal Statistical Society. Series A: Statistics in Society, 161(1), 13-32. https://doi.org/10.1111/1467-985X.00088
  • Skinner, Chris J., Humphreys, K. (1997). Instrumental variable estimation of gross flows in the presence of measurement error. Survey Methodology, 23(1), 53-60.
  • Nascimento, Silva, Skinner, Chris J. (1997). Variable selection for regression estimation in finite populations. Survey Methodology, 23(1), 23-32.
  • Skinner, Chris J. (1997). Comments on G.M. Fitzmaurice, A.F. Heath and D.R. Cox, ‘detecting overdispersion in large scale surveys: application to a study of education and social class in Britain’. Journal of the Royal Statistical Society. Series C: Applied Statistics, 46(4), 429-431. https://doi.org/10.1111/1467-9876.00081
  • Skinner, Chris J. (1997). Discussion of D. Steel, ‘producing monthly estimates of unemployment and employment according to the International Labour Office definition’. Journal of the Royal Statistical Society. Series A: Statistics in Society, 160(1), p. 39. https://doi.org/10.1111/1467-985X.00044
  • Skinner, Chris J. (1997). Discussion of J. B. Copas and H. G. Li, 'inference for non-random samples'. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 59(1), 77-78. https://doi.org/10.1111/1467-9868.00055
  • Skinner, Chris J., Rao, J. N. K. (1996). Estimation in dual frame surveys with complex designs. Journal of the American Statistical Association, 91(433), 349-356.
  • Skinner, Chris J. (1996). Comment of J. Shao,'invited discussion paper resampling methods in sample surveys. Statistics, 27(3-4), 203-237. https://doi.org/10.1080/02331889708802523
  • Skinner, Chris J., Coker, O. (1996). Regression analysis of complex survey data with missing values of a covariate. Journal of the Royal Statistical Society. Series A: Statistics in Society, 159(2), 265-274.
  • Silva, Nascimento, Skinner, Chris J. (1995). Estimating distribution functions with auxiliary information using poststratification. Journal of Official Statistics, 11(3), 277-294.
  • Skinner, Chris J., Marsh, Catherine, Openshaw, Stan, Wymer, Colin (1994). Disclosure control for census microdata. Journal of Official Statistics, 10(1), 31-51.
  • Sitter, R. R., Skinner, Chris J. (1994). Multi-way stratification by linear programming. Survey Methodology, 20(1), 65-73.
  • Skinner, Chris J. (1994). Comment on X-L Meng, ‘multiple-imputation inferences with uncongenial sources of input’. Statistical Science, 9(4), 561-563.
  • Skinner, Chris J., Holmes, D. J., Holt, D. (1994). Multiple frame sampling for multivariate stratification. International Statistical Review, 62(3), 333-347.
  • Marsh, Catherine, Dale, A., Skinner, Chris J. (1994). Safe data versus safe setting: access to microdata from the British Census. International Statistical Review, 62(1), 35-53.
    • Book
  • Chambers, R. L., Skinner, Chris J. (Eds.) (2003). Analysis of survey data. John Wiley & Sons.
    • Chapter
  • Turner, Malgorzata, Sturgis, Patrick, Martin, David, Skinner, Chris J. (2018). Can interviewer personality, attitudes and experience explain the design effect in face-to-face surveys? In Engel, U., Jann, B., Lynn, P., Scherpenzeel, A. & Stirgis, P. (Eds.), Improving Survey Methods: Lessons from Recent Research (pp. 72 - 85). Routledge.
  • Skinner, Chris J. (2016). Probability proportional to size (PPS) sampling. In Balakrishnan, N., Colton, T., Everitt, B., Piegorsch, W., Ruggeri, F., Teugels, J., Davidian, M., Kenett, R. S. & Molenberghs, G. (Eds.), Wiley StatsRef: Statistics Reference Online (pp. 1-5). John Wiley & Sons. https://doi.org/10.1002/9781118445112.stat03346.pub2 picture_as_pdf
  • Skinner, Chris J. (2009). Statistical disclosure control for survey data. In Pfeffermann, D. & Rao, C. R. (Eds.), Handbook of Statistics 29a: Sample Surveys: Design, Methods and Applications (pp. 381-396). Elsevier (Firm).
  • Skinner, Chris J. (2008). Assessing disclosure risk for record linkage. In Domingo-Ferrer, J. & Saygın, Y. (Eds.), Privacy in Statistical Databases: Unesco Chair in Data Privacy International Conference, Psd 2008 Istanbul, Turkey, September 24 (pp. 166-176). Springer Berlin / Heidelberg.
  • Skinner, Chris J. (2004). Méthodes pour protéger la confidentialité des données d’enquêtes. In Ardilly, P. (Ed.), Échantillonnage et Méthodes D'enquêtes (pp. 45-53). Dunod.
  • Skinner, Chris J., Holmes, D. J. (2003). Random effects models for longitudinal survey data. In Chambers, R. L. & Skinner, C. J. (Eds.), Analysis of Survey Data (pp. 205-219). John Wiley & Sons.
  • Skinner, Chris J. (2000). Dealing with measurement error in panel analysis. In Rose, D. (Ed.), Researching Social and Economic Change: the Uses of Household Panel Studies (pp. 113-125). Routledge.
  • Skinner, Chris J. (1998). Misclassification error. In Armitage, P. & Colton, T. (Eds.), Encyclopaedia of Biostatistics (pp. 2615-2621). John Wiley & Sons.
  • Kuha, Jouni, Skinner, Chris J. (1997). Categorical data analysis and misclassification. In Lyberg, L., Biemer, P., Collins, M., De Leeuw, E. D., Dippo, C., Schwarz, N. & Trewin, D. (Eds.), Survey Measurement and Process Quality (pp. 633-370). John Wiley & Sons.