Bayesian methods for modelling non-random missing data mechanisms in longitudinal studies

[1]  Andrew Gelman,et al.  Exploratory Data Analysis for Complex Models , 2004 .

[2]  David J. Spiegelhalter,et al.  Analysis of longitudinal binary data from multiphase sampling , 1998 .

[3]  Donald B. Rubin,et al.  Nested multiple imputation of NMES via partially incompatible MCMC , 2003 .

[4]  Nicky J Welton,et al.  Allowing for uncertainty due to missing data in meta‐analysis—Part 2: Hierarchical models , 2008, Statistics in medicine.

[5]  Peter Congdon Bayesian statistical modelling , 2002 .

[6]  William J. Browne,et al.  Implementation and performance issues in the Bayesian and likelihood fitting of multilevel models , 2000, Comput. Stat..

[7]  R. Christensen,et al.  A New Perspective on Priors for Generalized Linear Models , 1996 .

[8]  Garrett M. Fitzmaurice,et al.  Methods for Handling Dropouts in Longitudinal Clinical Trials , 2003 .

[9]  J. Kadane,et al.  Experiences in elicitation , 1998 .

[10]  S. Pocock,et al.  Coping with missing data in clinical trials: A model‐based approach applied to asthma trials , 2002, Statistics in medicine.

[11]  Joseph B. Kadane,et al.  Comparing Harm Done by Mobility and Class Absence: Missing Students and Missing Data , 2003 .

[12]  Bradley P. Carlin,et al.  Markov Chain Monte Carlo in Practice: A Roundtable Discussion , 1998 .

[13]  M. Kenward,et al.  A comparison of multiple imputation and doubly robust estimation for analyses with missing data , 2006 .

[14]  Geert Molenberghs,et al.  Missing Data in Clinical Studies , 2007 .

[15]  P. Diggle,et al.  Analysis of Longitudinal Data. , 1997 .

[16]  D. Rubin,et al.  On Jointly Estimating Parameters and Missing Data by Maximizing the Complete-Data Likelihood , 1983 .

[17]  Jeremy E. Oakley,et al.  Uncertain Judgements: Eliciting Experts' Probabilities , 2006 .

[18]  Nathaniel Schenker,et al.  Combining information from multiple surveys to enhance estimation of measures of health , 2007, Statistics in medicine.

[19]  S. Richardson,et al.  Hierarchical related regression for combining aggregate and individual data in studies of socio‐economic disease risk factors , 2007 .

[20]  S. Paddock Bayesian variable selection for longitudinal substance abuse treatment data subject to informative censoring , 2007 .

[21]  D J Spiegelhalter,et al.  Approximate cross‐validatory predictive checks in disease mapping models , 2003, Statistics in medicine.

[22]  M. Kenward,et al.  The analysis of longitudinal ordinal data with nonrandom drop-out , 1997 .

[23]  Thomas A. Louis,et al.  Graphical Elicitation of a Prior Distribution for a Clinical Trial , 1993 .

[24]  Susanne Rässler,et al.  A Non‐Iterative Bayesian Approach to Statistical Matching , 2003 .

[25]  D. Cox,et al.  An Analysis of Transformations , 1964 .

[26]  Ian Plewis,et al.  National Child Development Study and 1970 British Cohort Study Technical Report: Changes in the NCDS and BCS70 Populations and Samples over Time , 2004 .

[27]  David J. Lunn,et al.  A Bayesian toolkit for genetic association studies , 2006, Genetic epidemiology.

[28]  P. Rousseeuw,et al.  The Shape of Correlation Matrices , 1994 .

[29]  Jon Wakefield,et al.  Ecological inference for 2 × 2 tables , 2004 .

[30]  Roderick J. A. Little,et al.  Statistical Analysis with Missing Data , 1988 .

[31]  Daniel F Heitjan,et al.  An index of local sensitivity to nonignorable drop‐out in longitudinal modelling , 2005, Statistics in medicine.

[32]  M. Kenward,et al.  Every missingness not at random model has a missingness at random counterpart with equal fit , 2008 .

[33]  Joel B Greenhouse,et al.  Using prior distributions to synthesize historical evidence: comments on the Goodman–Sladky case study of IVIg in Guillain–Barré syndrome , 2005, Clinical trials.

[34]  Ken P Kleinman,et al.  Much Ado About Nothing , 2007, The American statistician.

[35]  Nathaniel Schenker,et al.  Combining Information From Two Surveys to Estimate County-Level Prevalence Rates of Cancer Risk Factors and Screening , 2007 .

[36]  A. Gelfand,et al.  Identifiability, Improper Priors, and Gibbs Sampling for Generalized Linear Models , 1999 .

[37]  A. Rotnitzky,et al.  Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis by DANIELS, M. J. and HOGAN, J. W , 2009 .

[38]  S Greenland,et al.  Basic methods for sensitivity analysis of biases. , 1996, International journal of epidemiology.

[39]  T. Raghunathan,et al.  Combining exposure information from various sources in an analysis of a case-control study , 1998 .

[40]  Roderick J. A. Little,et al.  Modeling the Drop-Out Mechanism in Repeated-Measures Studies , 1995 .

[41]  Leon Feinstein,et al.  Inequality in the Early Cognitive Development of British Children in the 1970 Cohort , 2003 .

[42]  J. Robins,et al.  Analysis of semi-parametric regression models with non-ignorable non-response. , 1997, Statistics in medicine.

[43]  A. Troxel,et al.  AN INDEX OF LOCAL SENSITIVITY TO NONIGNORABILITY , 2004 .

[44]  F. Peracchi,et al.  Survey response and survey characteristics: microlevel evidence from the European Community Household Panel , 2005 .

[45]  Geert Molenberghs,et al.  Selection models and pattern‐mixture models to analyse longitudinal quality of life data subject to drop‐out , 2002, Statistics in medicine.

[46]  Geert Molenberghs,et al.  Monotone missing data and pattern‐mixture models , 1998 .

[47]  Peter Green,et al.  Highly Structured Stochastic Systems , 2003 .

[48]  Joseph L Schafer,et al.  Analysis of Incomplete Multivariate Data , 1997 .

[49]  James R Carpenter,et al.  Sensitivity analysis after multiple imputation under missing at random: a weighting approach , 2007, Statistical methods in medical research.

[50]  N M Laird,et al.  Maximum likelihood analysis of generalized linear models with missing covariates , 1999, Statistical methods in medical research.

[51]  F. Vella Estimating Models with Sample Selection Bias: A Survey , 1998 .

[52]  Ian R White,et al.  Eliciting and using expert opinions about influence of patient characteristics on treatment effects: a Bayesian analysis of the CHARM trials , 2005, Statistics in medicine.

[53]  J. Schafer Multiple imputation: a primer , 1999, Statistical methods in medical research.

[54]  Harvey Goldstein,et al.  Multilevel models with multivariate mixed response types , 2009 .

[55]  Michael G Kenward,et al.  Multiple imputation: current perspectives , 2007, Statistical methods in medical research.

[56]  Joseph G Ibrahim,et al.  Bayesian Analysis for Generalized Linear Models with Nonignorably Missing Covariates , 2005, Biometrics.

[57]  Peter J. Diggle,et al.  Analysis of longitudinal data with drop‐out: objectives, assumptions and a proposal , 2007 .

[58]  Ian Plewis,et al.  The Contribution of Residential Mobility to Sample Loss in a Birth Cohort Study: Evidence from the First Two Waves of the UK Millennium Cohort Study , 2008 .

[59]  G Molenberghs,et al.  Sensitivity Analysis for Nonrandom Dropout: A Local Influence Approach , 2001, Biometrics.

[60]  N. Longford,et al.  Analysis of a long‐term study of neurotic disorder, with insights into the process of non‐response , 2006 .

[61]  Gareth O. Roberts,et al.  Convergence assessment techniques for Markov chain Monte Carlo , 1998, Stat. Comput..

[62]  Andrew Gelman,et al.  R2WinBUGS: A Package for Running WinBUGS from R , 2005 .

[63]  D. Rubin Multiple Imputation After 18+ Years , 1996 .

[64]  H. Boshuizen,et al.  Multiple imputation of missing blood pressure covariates in survival analysis. , 1999, Statistics in medicine.

[65]  S. Lipsitz,et al.  Missing-Data Methods for Generalized Linear Models , 2005 .

[66]  Mario Peruggia,et al.  On the variability of case-deletion importance sampling weights in the Bayesian linear model , 1997 .

[67]  S. Chib,et al.  Bayesian analysis of binary and polychotomous response data , 1993 .

[68]  G Molenberghs,et al.  Parametric models for incomplete continuous and categorical longitudinal data , 1999, Statistical methods in medical research.

[69]  A. Gelman Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper) , 2004 .

[70]  H. Goldstein,et al.  Patterns of Attainment. , 1978 .

[71]  D. Collett Modelling Binary Data , 1991 .

[72]  Matthew Hotopf,et al.  Using number of failed contact attempts to adjust for non‐ignorable non‐response , 2006 .

[73]  M. Kenward,et al.  Informative dropout in longitudinal data analysis (with discussion) , 1994 .

[74]  D. S. Bunch,et al.  Estimability in the Multinomial Probit Model , 1989 .

[75]  I. Plewis,et al.  Modelling non‐response in the National Child Development Study , 2006 .

[76]  Peter E. Rossi,et al.  An exact likelihood analysis of the multinomial probit model , 1994 .

[77]  Andrew Gelman,et al.  Diagnostics for multivariate imputations , 2007 .

[78]  Jun S. Liu,et al.  Metropolized independent sampling with comparisons to rejection sampling and importance sampling , 1996, Stat. Comput..

[79]  Gabriele B. Durrant,et al.  Using data augmentation to correct for non‐ignorable non‐response when surrogate data are available: an application to the distribution of hourly pay , 2006 .

[80]  Xiao-Li Meng,et al.  Applications of multiple imputation in medical studies: from AIDS to NHANES , 1999, Statistical methods in medical research.

[81]  P. Allison Multiple Imputation for Missing Data , 2000 .

[82]  Sylvia Richardson,et al.  Using Bayesian graphical models to model biases in observational studies and to combine multiple sources of data: application to low birth weight and water disinfection by‐products , 2009 .

[83]  Sylvia Richardson,et al.  Improving ecological inference using individual‐level data , 2006, Statistics in medicine.

[84]  C. Robert,et al.  Deviance information criteria for missing data models , 2006 .

[85]  G. King,et al.  Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation , 2001, American Political Science Review.

[86]  Jun S. Liu,et al.  Sequential Imputations and Bayesian Missing Data Problems , 1994 .

[87]  David B. Dunson,et al.  Bayesian Data Analysis , 2010 .

[88]  Andrew M. Jones,et al.  Health‐related non‐response in the British Household Panel Survey and European Community Household Panel: using inverse‐probability‐weighted estimators in non‐linear models , 2006 .

[89]  J. Schafer Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ , 2003 .

[90]  N M Laird,et al.  Model-based approaches to analysing incomplete longitudinal and failure time data. , 1997, Statistics in medicine.

[91]  Anthony N. Pettitt,et al.  A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants , 2006 .

[92]  Joseph B. Kadane,et al.  Subjective Bayesian analysis for surveys with missing data , 1993 .

[93]  Daniel O Scharfstein,et al.  Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes. , 2003, Biostatistics.

[94]  S. van Buuren,et al.  Flexibele multiple imputation by chained equations of the AVO-95 Survey , 1999 .

[95]  Bradley P. Carlin,et al.  Bayesian measures of model complexity and fit , 2002 .

[96]  D. Dunson,et al.  Bayesian latent variable models for clustered mixed outcomes , 2000 .

[97]  Ian R White,et al.  Allowing for uncertainty due to missing data in meta‐analysis—Part 1: Two‐stage methods , 2008, Statistics in medicine.

[98]  Geert Verbeke,et al.  Multiple Imputation for Model Checking: Completed‐Data Plots with Missing and Latent Data , 2005, Biometrics.

[99]  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.

[100]  J. Schafer,et al.  Missing data: our view of the state of the art. , 2002, Psychological methods.

[101]  Geert Molenberghs,et al.  Sensitivity Analysis of Continuous Incomplete Longitudinal Outcomes , 2003 .

[102]  Michael G. Kenward,et al.  Using Hierarchical Likelihood for Missing Data Problems , 2007 .

[103]  A. Brix Bayesian Data Analysis, 2nd edn , 2005 .

[104]  E. Boyko,et al.  The millennium Cohort Study: a 21-year prospective cohort study of 140,000 military personnel. , 2002, Military medicine.

[105]  Nicholas J. Horton,et al.  Multiple Imputation in Practice , 2001 .

[106]  J. Schafer,et al.  A comparison of inclusive and restrictive strategies in modern missing data procedures. , 2001, Psychological methods.

[107]  Andrew Gelman,et al.  General methods for monitoring convergence of iterative simulations , 1998 .

[108]  D. Rubin INFERENCE AND MISSING DATA , 1975 .

[109]  Ulrich Rendtel,et al.  Extent and Determinants of Panel Attrition in the European Community Household Panel , 2005 .

[110]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[111]  I. White,et al.  Eliciting and using expert opinions about dropout bias in randomized controlled trials , 2007, Clinical trials.

[112]  D. Rubin,et al.  Fully conditional specification in multivariate imputation , 2006 .

[113]  Sander Greenland,et al.  Multiple‐bias modelling for analysis of observational data , 2005 .

[114]  M. Kenward Selection models for repeated measurements with non-random dropout: an illustration of sensitivity. , 1998, Statistics in medicine.

[115]  David J. Lunn,et al.  Generic reversible jump MCMC using graphical models , 2009, Stat. Comput..

[116]  Peter E. Rossi,et al.  A Bayesian analysis of the multinomial probit model with fully identified parameters , 2000 .

[117]  Bradley P. Carlin,et al.  Markov Chain Monte Carlo conver-gence diagnostics: a comparative review , 1996 .

[118]  Jonathan J. Forster,et al.  Model‐based inference for categorical survey data subject to non‐ignorable non‐response , 1998 .

[119]  Robert E. Kass,et al.  A default conjugate prior for variance components in generalized linear mixed models (comment on article by Browne and Draper) , 2006 .

[120]  R. Little Pattern-Mixture Models for Multivariate Incomplete Data , 1993 .

[121]  S. Chib,et al.  Analysis of multivariate probit models , 1998 .

[122]  I. Plewis Non‐Response in a Birth Cohort Study: The Case of the Millennium Cohort Study , 2007 .

[123]  B. R. Dansie PARAMETER ESTIMABILITY IN THE MULTINOMIAL PROBIT MODEL , 1985 .

[124]  D. Spiegelhalter,et al.  Bayesian Analysis of Realistically Complex Models , 1996 .

[125]  H. Goldstein,et al.  Social Factors associated with changes in Educational Attainment between 7 and 11 Tears of Age , 1976 .