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Year: 2010

  • Langkamp, D. L., Lehman, A. & Lemeshow, S. (2010). Techniques for Handling Missing Data in Secondary Analyses of Large Surveys. Academic Pediatrics, 10(3), 205-210. [More] [Bibtex]
  • Lee, K., Daniels, M. J. & Sargent, D. J. (2010). Causal Effects of Treatments for Informative Missing Data due to Progression/Death. Journal of the American Statistical Association, 105(491), 912-929. [More] [Bibtex]
  • Leung, J., Dwyer, J., Hibberd, P., Jacques, P. & Rand, W. (2010). Imputation methods for handling missing dietary supplement dosage data.. J Ren Nutr, 20(5), 342-7. [More] [Bibtex]
  • Leung, J., Dwyer, J., Hibberd, P., Jacques, P. & Rand, W. (2010). Imputation Methods for Handling Missing Dietary Supplement Dosage Data. Journal of Renal Nutrition, 20(5), 342-347. [More] [Bibtex]
  • Lin, T. H. (2010). A comparison of multiple imputation with EM algorithm and MCMC method for quality of life missing data. Quality & Quantity, 44(2), 277-287. [More] [Bibtex]
  • Mackinnon, A. (2010). The use and reporting of multiple imputation in medical research - a review. Journal of Internal Medicine, 268(6), 586-593. [More] [Bibtex]
  • Marston, L., Carpenter, J. R., Walters, K. R., Morris, R. W., Nazareth, I. & Petersen, I. (2010). Issues in multiple imputation of missing data for large general practice clinical databases. Pharmacoepidemiology and Drug Safety, 19(6), 618-626. [More] [Bibtex]
  • McCandless, L. C., Richardson, S. & Best, N. (2010). Reducing Bias From Several Missing Confounders Using External Validation Data. American Journal of Epidemiology, 171, S145-S145. [More] [Bibtex]
  • O'Connor, A. B. (2010). LOCF approach to handling missing data overestimates the pain score improvement of drop-outs.. J Pain, 11(5), 500-1;. [More] [Bibtex]
  • O'Connor, A. B. (2010). LOCF Approach to Handling Missing Data Overestimates the Pain Score Improvement of Drop-Outs. Journal of Pain, 11(5), 500-501. [More] [Bibtex]
  • Palmer, R. F. & Royall, D. R. (2010). Missing Data? Plan on It!. Journal of the American Geriatrics Society, 58, S343-S348. [More] [Bibtex]
  • Poon, W. Y. & Wang, H. B. (2010). Analysis of a Two-Level Structural Equation Model With Missing Data. Sociological Methods & Research, 39(1), 25-55. [More] [Bibtex]
  • Qi, L. H., Wang, Y. F. & He, Y. L. (2010). A comparison of multiple imputation and fully augmented weighted estimators for Cox regression with missing covariates. Statistics In Medicine, 29(25), 2592-2604. [More] [Bibtex]
  • Qu, A., Lindsay, B. G. & Lu, L. (2010). Highly Efficient Aggregate Unbiased Estimating Functions Approach for Correlated Data With Missing at Random. Journal of the American Statistical Association, 105(489), 194-204. [More] [Bibtex]
  • Rajan, K., de Leon, C. M. & Evans, D. (2010). Statistical Methods For Non-ignorable Missing Data and Death In Epidemiologic Studies. American Journal of Epidemiology, 171, S97-S97. [More] [Bibtex]
  • Rajan, K. B. & Leurgans, S. E. (2010). Joint modeling of missing data due to non-participation and death in longitudinal aging studies. Statistics In Medicine, 29(21), 2260-2268. [More] [Bibtex]
  • Rizopoulos, D., Verbeke, G. & Molenberghs, G. (2010). Multiple-Imputation-Based Residuals and Diagnostic Plots for Joint Models of Longitudinal and Survival Outcomes. Biometrics, 66(1), 20-29. [More] [Bibtex]
  • Qi, L., Wang, Y. & He, Y. (2010). A comparison of multiple imputation and fully augmented weighted estimators for Cox regression with missing covariates. Statistics in Medicine, 29, 2592–2604. [More] [Online version] [Bibtex]
  • Lu, K., Jiang, L. & Tsiatis, A. A. (2010). Multiple Imputation Approaches for the Analysis of Dichotomized Responses in Longitudinal Studies with Missing Data. Biometrics, 66, 1202-1208. [More] [Online version] [Bibtex]
  • Marshall, A., Altman, D. G. & Holder, R. L. (2010). Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study. BMC Medical Research Methodology, 10, 112. [More] [Online version] [Bibtex]
  • Marshall, A., Altman, D. G., Holder, R. L. & Royston, P. (2010). Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study. BMC Medical Research Methodology, 10, 7. [More] [Online version] [Bibtex]
  • White, I. R. & Carlin, J. B. (2010). Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values. Statistics in Medicine, 29, 2920-2931. [More] [Online version] [Bibtex]
  • Vansteelandt, S., Carpenter, J. & Kenward, M. (2010). Analysis of incomplete data using inverse probability weighting and doubly robust estimators. Methodology, 6, 37-49. [More] [Bibtex]
  • Lee, K. J. & Carlin, J. B. (2010). Multiple Imputation for Missing Data: Fully Conditional Specification Versus Multivariate Normal Imputation. American Journal of Epidemiology, 171(5), 624-632. [More] [Online version] [Bibtex]
  • Aalen, O. O. & Gunnes, N. (2010). A dynamic approach for reconstructing missing longitudinal data using the linear increments model. Biostatistics, 1-20. [More] [Online version] [Bibtex]
Results 126 - 150 of 701