David Haziza
Département de mathématiques et de statistique

Papers published or accepted

[20] YUNG, W. & HAZIZA, D. (2011). Comment on the paper "Bias-adjustment and calibration of jackknife variance estimator in the presence of non-response." To appear in Journal of Statistical Planning and Inference.

[19] CHAUVET, G. & HAZIZA, D. (2012). Fully efficient estimation of coefficients of correlation in the presence of imputed survey data. To appear in the Canadian Journal of Statistics.

[18] HAZIZA, D., HIDIROGLOU, M.A. & RAO, J.N.K. (2011). Comparisons of variance estimators in two-phase sampling: an empirical investigation. Pakistan Journal of Statistics, 27, 477-492 (Invited submission for a special issue in honour of Ken Brewer).

[17] CHAUVET, G., DEVILLE J.C. & HAZIZA, D. (2011). On balanced random imputation in surveys. Biometrika, 98, 459-471.

[16] BEAUMONT, J.-F., HAZIZA, D. & BOCCI, C. (2011). Variance estimation under auxiliary value imputation. Statistica Sinica, 21, 515-538.

[15] HAZIZA, D. & RAO, J.N.K. (2010). Variance estimation in two-stage sampling under imputation for missing survey data. Journal of Statistical Theory and Practice, 4, 827-848 (Invited submission for H.C. Gupta memorial special issue).

[14] TILLÉ, Y. & HAZIZA, D. (2010). An interesting property of the entropy of some sampling designs. Survey Methodology, 36, 229-231.

[13] HAZIZA, D., CHAUVET, G. & DEVILLE J.C. (2010). A note on sampling and estimation in the presence of cut-off sampling. Australian and New Zealand Journal of Statistics, 52, 303-319.

[12] HAZIZA, D., THOMPSON, K.J., YUNG, W. (2010). The effect of nonresponse adjustments on variance estimation. Survey Methodology, 36, 35-43.

[11] HAZIZA, D. (2009). Imputation and inference in the presence of missing data. Handbook of Statistics, Volume 29, Sample Surveys: Theory Methods and Inference, Editors: C.R. Rao and D. Pfeffermann, 215-246.

[10] HIDIROGLOU, M.A., RAO, J.N.K. & HAZIZA, D. (2009). Variance estimation in two phase sampling. Australian and New Zealand Journal of Statistics, 51, 127-141.

[9] HAZIZA, D., MECATTI, F. & RAO, J.N.K. (2008). Approximate variance estimators under the Rao-Sampford design. Metron, 66, 91-108(Invited submission for a special issue in survey sampling).

[8] HAZIZA, D. (2007). Variance estimation for a ratio in the presence of imputed data. Survey Methodology, 33, 159-166.

[7] HAZIZA, D. & KUROMI, G. (2007). Handling item nonresponse in surveys. Journal of Case Studies in Business, Industry and Government statistics, 1, 102-118.

[6] HAZIZA, D. & BEAUMONT, J-F. (2007). On the construction of imputation classes in surveys. International Statistical Review, 75, 25-43.

[5] HAZIZA, D. & RAO, J. N. K. (2006). A nonresponse model approach to inference under imputation for missing survey data, Survey Methodology, 32, 53-64.

[4] HAZIZA, D. (2005). Inférence en présence d’imputation simple dans les enquêtes: un survol,Journal de la Société Française de Statistique, 146, 69-118.

[3] HAZIZA, D. & RAO, J. N. K. (2005). Inference for domains under imputation for missing data, The Canadian Journal of Statistics, 33, 149-161.

[2] ARAGON, Y., HAZIZA, D. & RUIZ-GAZEN, A. (2005). Les simulations dans l'enseignement des sondages avec le logiciel Genesis sous SAS et la bibliothèque Sondages sous R, Modulad,32, 86-91.

[1] HAZIZA, D. & RAO, J. N. K. (2003). Inference for population means under unweighted imputation for missing survey data, Survey Methodology, 29, 81-90.

Papers submitted or in preparation

DONGMO JIONGO, V., HAZIZA, D. & DUCHESNE, P. (2011). Controlling the bias of robust small area estimators. In revision for Biometrika.

BEAUMONT, J.-F., HAZIZA, D. & RUIZ-GAZEN, A. (2011). A unified approach to robust estimation in finite population sampling. In revision for Biometrika.

CHAPUT, H., CHAUVET, G, HAZIZA, D., SOLARD, J. & SALEMBIER, L. (2011). Joint imputation procedures for categorical variables with application to the French Wealth Survey. In revision for the Journal of the Royal Statistical Society, Series C.

HAZIZA, D. & PICARD, F. (2009). On doubly robust point and variance estimation in the presence of imputed data. Submitted after the second revision for the Canadian Journal of Statistics.

HAZIZA, D., NAMBEU, C.-O. & CHAUVET, G. (2010). Single imputation procedures when the population contains a large amount of zeroes. In revision for Computational Statistics and Data Analysis.

KIM, J.K. & HAZIZA, D. (2010) Doubly robust inference with missing survey data. Submitted.

CHAUVET, G., DEVILLE J.C. & HAZIZA, D. (2010), Adapting the Cube algorithm for balanced imputation in surveys. Submitted.

CHAUVET, G. & HAZIZA, D. (2009). Imputation or preserving relationships.

Books

GUILBERT, P., HAZIZA, D., RUIZ-GAZEN, A.M. & TILLÉ, Y, (éditeurs). (2008). Méthodes de Sondages. Dunod.

Book chapters

HAZIZA, D. & BEAUMONT, J-F. (2005), Estimation simplifiée de la variance dans le cas de l’échantillonnage à deux phases in Méthodes d’enquêtes et sondages, Lavallée, P. and Rivest, L.P., editors, 372-377. Dunod.

HAZIZA, D. & RAO, J. N. K. (2004). Inférence pour des statistique bivariées en présence d’imputation dans le cas d’enquêtes stratifiées à degrés multiples, inÉchantillonnage et méthodes d’enquêtes, Ardilly, P. Editor, 189-196. Dunod.

Conference proceedings

BOISTARD, H., CHAUVET, G. & HAZIZA, D. (2012). Consistance sous un modèle de réponse de la fonctiond de répartition estimée en présence de données manquantes. To appear in the Proceedings of the JMS 2012.

HAZIZA, D., DONGMO JIONGO, V. & DUCHESNE, P. (2012). Triple robustesse en présence de données imputées dans les enquêtes. To appear in the Proceedings of the JMS 2012.

KIM, J.K. & HAZIZA, D. (2010). Doubly robust inference with missing data in survey sampling. Proceedings of the Survey Research Methods, American Statistical Association.

HAZIZA, D. (2010). Resampling methods for variance estimation in the presence of missing survey data. Proceedings of the conference of the annual conference of the Italian Statistical Society.

BEAUMONT, J.-F., HAZIZA, D. & RUIZ-GAZEN, A. (2009). A unified approach to robust estimation in finite population sampling. Proceedings of the coference of the International Statistical Institute. Durbin. South Africa.

HAZIZA, D. & PICARD, F. (2008), Jackknife variance estimation in the presence of imputed data. Proceedings of the Workshop on Calibration and Estimation in Surveys.

HAZIZA, D., KUROMI, G. & BÉRUBÉ, J. (2007), Sampling and estimation in the the presence of tax data in business surveys. Proceedings of the International Conference on Establishment Surveys II, CD-ROM.

HAZIZA, D. (2006), Estimation en présence de données fiscales dans les enquêtes économiques. Proceedings of the Journées de Statistique de la Société Française de Statistique, CD-ROM.

HAZIZA, D. & RAO, J. N. K. (2005), Une approche par modèle de non-réponse pour l’inférence en présence de données imputées, Proceedings of the Journées de Méthodologie Statistique 2005. Disponible sur la page http://jms.insee.fr/site/.

HAZIZA, D., MECATTI, F. & RAO, J. N. K. (2004), Comparison of variance estimators under Rao-Sampford method: a simulation study. Proceedings of the Survey Methods Section, American Statistical Association, CD-Rom.

HAZIZA, D. (2003), GENESIS, a methodological and pedagogical tool, Proceedingsof the Survey Methods Section, American Statistical Association, CD-Rom.

BEAUMONT, J-F, HAZIZA, D., MITCHELL, C. & RANCOURT, E. (2003), New tools at Statistics Canada to measure and evaluate the impact of nonresponse and imputation, Proceedings of the 2003 FCSM conference.

HAZIZA, D. & RAO, J. N. K. (2001), Inference for regression coefficients under imputation for missing data, Proceedings of the Survey Methods Section, Statistical Society of Canada, 61-66.

HAZIZA, D. & RAO, J. N. K. (2001), Model-assisted approach to inference for totals in cluster sampling under imputation for missing data, Proceedingsof the Survey Methods Section, American Statistical Association, CD-Rom.

HAZIZA, D., CHOW, O., CHARBONNIER, C. and BEAUMONT, J.F. (2001), Construction of Imputation Cells in the Canadian Labour Force Survey, Proceedings of Statistics Canada Symposium 2001, CD-Rom.

HAZIZA, D. and RAO, J. N. K. (2000), Inference for domain means under imputation for missing data, Proceedings of the Survey Methods Section, Statistical Society of Canada, 197-202.

Published in the Imputation Bulletin

HAZIZA, D. (2007). Frameworks for variance estimation in the presence of imputed data, The Imputation Bulletin, vol 7, no 1.

HAZIZA, D. (2006). Simulation studies in the presence of nonresponse and imputation, The Imputation Bulletin, vol 6, no 1.

HAZIZA, D. & RANCOURT, E. (2004). Variance estimation under the two-phase imputation model approach, The Imputation Bulletin, vol 4, no 1.

HAZIZA, D. (2003). Proc MI and Proc MIANALYZE in SAS, The Imputation Bulletin, vol 3, no 2.

HAZIZA, D. (2002). Distortion of distributions, The Imputation Bulletin, vol 2, no 2.

HAZIZA, D. (2002). GENESIS, The Imputation Bulletin, vol 2, no 2.

HAZIZA, D. (2002). Imputation classes, The Imputation Bulletin, vol 2, no 1.

HAZIZA, D. (2001). The risks of imputation, The Imputation Bulletin, vol 1, no 2.

HAZIZA, D. (2001). Why do we impute?, The Imputation Bulletin, vol 1, no 1.