LSE creators

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, Uwe, Jann, Ben, Lynn, Peter, Scherpenzeel, Annette, Stirgis, Patrick (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, Theodore, Everitt, Brian, Piegorsch, Walter, Ruggeri, Fabrizio, Teugels, Jef, Davidian, Marie, Kenett, Ron S., Molenberghs, Geert (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, Josep, Saygın, Yücel (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, Pascal (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, Chris 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, David (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, Lars, Biemer, Paul, Collins, Martin, De Leeuw, Edith D., Dippo, Cathryn, Schwarz, Norbert, Trewin, Dennis (Eds.), Survey Measurement and Process Quality (pp. 633-370). John Wiley & Sons.