Multiple imputation of discrete and continuous data by fully conditional specification
暂无分享,去创建一个
[1] David Maxwell Chickering,et al. Dependency Networks for Inference, Collaborative Filtering, and Data Visualization , 2000, J. Mach. Learn. Res..
[2] Mariza de Andrade,et al. Imputation methods for missing data for polygenic models , 2003, BMC Genetics.
[3] Stef van Buuren,et al. Pubertal Development in The Netherlands 1965–1997 , 2001, Pediatric Research.
[4] Jürgen Unützer,et al. A comparison of imputation methods in a longitudinal randomized clinical trial , 2005, Statistics in medicine.
[5] Maher M El-Masri,et al. Handling missing data in self-report measures. , 2005, Research in nursing & health.
[6] Geert Molenberghs,et al. Direct likelihood analysis versus simple forms of imputation for missing data in randomized clinical trials , 2005, Clinical trials.
[7] Pierre Côté,et al. Methods to Account for Attrition in Longitudinal Data: Do They Work? A Simulation Study , 2005, European Journal of Epidemiology.
[8] Arthur B. Kennickell,et al. Imputation of the 1989 Survey of Consumer Finances: Stochastic Relaxation and Multiple Imputation , 1997 .
[9] D. Rubin. Multiple Imputation After 18+ Years , 1996 .
[10] D B Rubin,et al. Multiple Imputation for Multivariate Data with Missing and Below‐Threshold Measurements: Time‐Series Concentrations of Pollutants in the Arctic , 2001, Biometrics.
[11] L. A. Goodman. The Multivariate Analysis of Qualitative Data: Interactions among Multiple Classifications , 1970 .
[12] W. Tierney,et al. Multiple imputation in public health research , 2001, Statistics in medicine.
[13] T. Speed,et al. Characterizing a joint probability distribution by conditionals , 1993 .
[14] Jan B Oostenbrink,et al. The analysis of incomplete cost data due to dropout. , 2005, Health economics.
[15] D B Rubin,et al. Multiple imputation in health-care databases: an overview and some applications. , 1991, Statistics in medicine.
[16] G. C. Wei,et al. Applications of multiple imputation to the analysis of censored regression data. , 1991, Biometrics.
[17] M Y Hu,et al. Performance of a general location model with an ignorable missing-data assumption in a multivariate mental health services study. , 1999, Statistics in medicine.
[18] S Greenland,et al. A critical look at methods for handling missing covariates in epidemiologic regression analyses. , 1995, American journal of epidemiology.
[19] D. Rubin,et al. Inference from Iterative Simulation Using Multiple Sequences , 1992 .
[20] D. Rubin. Multiple imputation for nonresponse in surveys , 1989 .
[21] P. Allison. Missing data techniques for structural equation modeling. , 2003, Journal of abnormal psychology.
[22] J. Schafer,et al. A comparison of inclusive and restrictive strategies in modern missing data procedures. , 2001, Psychological methods.
[23] L Ryan,et al. Semiparametric Regression Analysis of Interval‐Censored Data , 2000, Biometrics.
[24] Jeremy MG Taylor,et al. Partially parametric techniques for multiple imputation , 1996 .
[25] S. Crawford,et al. A comparison of anlaytic methods for non-random missingness of outcome data. , 1995, Journal of clinical epidemiology.
[26] Donald B. Rubin,et al. Statistical Matching Using File Concatenation With Adjusted Weights and Multiple Imputations , 1986 .
[27] J. Besag. Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .
[28] B. Arnold,et al. Conditional specification of statistical models , 1999 .
[29] Roderick J. A. Little. Regression with Missing X's: A Review , 1992 .
[30] D. Rubin,et al. Fully conditional specification in multivariate imputation , 2006 .
[31] Alan Olinsky,et al. The comparative efficacy of imputation methods for missing data in structural equation modeling , 2003, Eur. J. Oper. Res..
[32] Xiao-Li Meng,et al. Multiple-Imputation Inferences with Uncongenial Sources of Input , 1994 .
[33] Andrew Gelman,et al. Diagnostics for multivariate imputations , 2007 .
[34] A Lawrence Gould,et al. COMPARISON OF ALTERNATIVE STRATEGIES FOR ANALYSIS OF LONGITUDINAL TRIALS WITH DROPOUTS , 2002, Journal of biopharmaceutical statistics.
[35] R. Tibshirani,et al. Generalized Additive Models , 1991 .
[36] Lynn McCleary,et al. Using Multiple Imputation for Analysis of Incomplete Data in Clinical Research , 2002, Nursing research.
[37] Hakan Demirtas,et al. Modeling Incomplete Longitudinal Data , 2004 .
[38] G Molenberghs,et al. Analysis of incomplete public health data. , 1999, Revue d'epidemiologie et de sante publique.
[39] J. Schafer,et al. Missing data: our view of the state of the art. , 2002, Psychological methods.
[40] Donald B. Rubin,et al. Nested multiple imputation of NMES via partially incompatible MCMC , 2003 .
[41] Craig K. Enders,et al. Missing Data in Educational Research: A Review of Reporting Practices and Suggestions for Improvement , 2004 .
[42] Ian R White,et al. Comparison of imputation and modelling methods in the analysis of a physical activity trial with missing outcomes. , 2004, International journal of epidemiology.
[43] B. Arnold,et al. Compatible Conditional Distributions , 1989 .
[44] R Little,et al. Intent-to-treat analysis for longitudinal studies with drop-outs. , 1996, Biometrics.
[45] Fritz Scheuren,et al. Multiple Imputation , 2005 .
[46] J. Schafer. Multiple imputation: a primer , 1999, Statistical methods in medical research.
[47] Recail M Yucel,et al. Imputation of Binary Treatment Variables With Measurement Error in Administrative Data , 2005 .
[48] S. van Buuren,et al. Multivariate Imputation by Chained Equations : Mice V1.0 User's manual , 2000 .
[49] D. Massart,et al. Dealing with missing data: Part II , 2001 .
[50] S. Lipsitz,et al. Missing-Data Methods for Generalized Linear Models , 2005 .
[51] Patrick Royston,et al. Multiple Imputation of Missing Values: Update of Ice , 2005 .
[52] William A Ghali,et al. Multiple imputation versus data enhancement for dealing with missing data in observational health care outcome analyses. , 2002, Journal of clinical epidemiology.
[53] David L Streiner,et al. The Case of the Missing Data: Methods of Dealing with Dropouts and other Research Vagaries , 2002, Canadian journal of psychiatry. Revue canadienne de psychiatrie.
[54] D. Rubin,et al. Statistical Analysis with Missing Data. , 1989 .
[55] W Pan,et al. A Multiple Imputation Approach to Linear Regression with Clustered Censored Data , 2001, Lifetime data analysis.
[56] D. Novins,et al. Methods for addressing missing data in psychiatric and developmental research. , 2005, Journal of the American Academy of Child and Adolescent Psychiatry.
[57] Stuart R. Lipsitz,et al. A note on reducing the bias of the approximate Bayesian bootstrap imputation variance estimator , 2005 .
[58] Steven G. Heeringa. Multivariate imputation of coarsened survey data on household wealth. , 2000 .
[59] Nicholas J. Horton,et al. A Potential for Bias When Rounding in Multiple Imputation , 2003 .
[60] Stef van Buuren,et al. A toolkit in SAS for the evaluation of multiple imputation methods , 2003 .
[61] M. Chavance,et al. Handling Missing Items in Quality of Life Studies , 2004 .
[62] Lawrence Joseph,et al. Multiple Imputation to Account for Missing Data in a Survey: Estimating the Prevalence of Osteoporosis , 2002, Epidemiology.
[63] N T Longford. Multilevel analysis with messy data , 2001, Statistical methods in medical research.
[64] John W Seaman,et al. Multiple imputation techniques in small sample clinical trials , 2006, Statistics in medicine.
[65] J. Wanzer Drane,et al. Multiple Imputation For Missing Ordinal Data , 2005 .
[66] Susan M. Paddock. Bayesian nonparametric multiple imputation of partially observed data with ignorable nonresponse , 2002 .
[67] Trivellore E Raghunathan,et al. What do we do with missing data? Some options for analysis of incomplete data. , 2004, Annual review of public health.
[68] J. Heckman. The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models , 1976 .
[69] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[70] Xiao-Li Meng,et al. Applications of multiple imputation in medical studies: from AIDS to NHANES , 1999, Statistical methods in medical research.
[71] Harri Niska,et al. Methods for imputation of missing values in air quality data sets , 2004 .
[72] Sati Mazumdar,et al. Estimating treatment effects from longitudinal clinical trial data with missing values: comparative analyses using different methods , 2004, Psychiatry Research.
[73] Joseph L Schafer,et al. Analysis of Incomplete Multivariate Data , 1997 .
[74] R. Little. Missing-Data Adjustments in Large Surveys , 1988 .
[75] S. Chib,et al. Bayesian analysis of binary and polychotomous response data , 1993 .
[76] D. Russell,et al. Missing data: a review of current methods and applications in epidemiological research , 2004 .
[77] Frank E. Harrell,et al. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2001 .
[78] H. Stern,et al. The use of multiple imputation for the analysis of missing data. , 2001, Psychological methods.
[79] Andrew Briggs,et al. Missing... presumed at random: cost-analysis of incomplete data. , 2003, Health economics.
[80] J. Schafer. Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ , 2003 .
[81] Stef van Buuren,et al. Continuing Positive Secular Growth Change in the Netherlands 1955–1997 , 2000, Pediatric Research.
[82] A. Gelman. Parameterization and Bayesian Modeling , 2004 .
[83] H. Boshuizen,et al. Multiple imputation of missing blood pressure covariates in survival analysis. , 1999, Statistics in medicine.
[84] P. Patrician. Multiple imputation for missing data. , 2002, Research in nursing & health.
[85] W Pan,et al. A Multiple Imputation Approach to Cox Regression with Interval‐Censored Data , 2000, Biometrics.
[86] B. Arnold,et al. Conditionally Specified Distributions: An Introduction (with comments and a rejoinder by the authors) , 2001 .
[87] John Van Hoewyk,et al. A multivariate technique for multiply imputing missing values using a sequence of regression models , 2001 .
[88] J.P.L. Brand,et al. Development, Implementation and Evaluation of Multiple Imputation Strategies for the Statistical Analysis of Incomplete Data Sets , 1999 .
[89] S M Kneipp,et al. Handling Missing Data in Nursing Research With Multiple Imputation , 2001, Nursing research.
[90] T. Pigott,et al. Missing Predictors in Models of Effect Size , 2001, Evaluation & the health professions.
[91] J. Cerhan,et al. Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits , 2004, Environmental Health Perspectives.
[92] Roderick J. A. Little,et al. Statistical Analysis with Missing Data: Little/Statistical Analysis with Missing Data , 2002 .
[93] Song Yang,et al. Imputation of missing data when measuring physical activity by accelerometry. , 2005, Medicine and science in sports and exercise.
[94] Margaret S. Pepe,et al. The relationship between hot-deck multiple imputation and weighted likelihood. , 1997, Statistics in medicine.
[95] James M. Tanner,et al. Variations in pattern of pubertal changes in girls. , 1969 .
[96] Nicholas J. Horton,et al. Multiple Imputation in Practice , 2001 .
[97] Jos Twisk,et al. Attrition in longitudinal studies. How to deal with missing data. , 2002, Journal of clinical epidemiology.
[98] William S. Reece,et al. Imputation of Missing Values When the Probability of Response Depends on the Variable Being Imputed , 1982 .
[99] Harrie C. M. Vorst,et al. Alternative Missing Data Techniques to Grade Point Average: Imputing Unavailable Grades , 2002 .