Bayesian multiple imputation for missing multivariate longitudinal data from a Parkinson's disease clinical trial

In Parkinson's disease (PD) clinical trials, Parkinson's disease is studied using multiple outcomes of various types (e.g. binary, ordinal, continuous) collected repeatedly over time. The overall treatment effects across all outcomes can be evaluated based on a global test statistic. However, missing data occur in outcomes for many reasons, e.g. dropout, death, etc., and need to be imputed in order to conduct an intent-to-treat analysis. We propose a Bayesian method based on item response theory to perform multiple imputation while accounting for multiple sources of correlation. Sensitivity analysis is performed under various scenarios. Our simulation results indicate that the proposed method outperforms standard methods such as last observation carried forward and separate random effects model for each outcome. Our method is motivated by and applied to a Parkinson's disease clinical trial. The proposed method can be broadly applied to longitudinal studies with multiple outcomes subject to missingness.

[1]  M. R. Novick,et al.  Statistical Theories of Mental Test Scores. , 1971 .

[2]  Z. Schwab,et al.  Projection technique for evaluating surgery in Parkinson’s disease , 1969 .

[3]  F. Lord.  Applications of Item Response Theory To Practical Testing Problems , 1980 .

[4]  P. O'Brien.  Procedures for comparing samples with multiple endpoints. , 1984, Biometrics.

[5]  T. W. Anderson,et al.  An Introduction to Multivariate Statistical Analysis , 1959 .

[6]  N L Geller,et al.  The analysis of multiple endpoints in clinical trials. , 1987, Biometrics.

[7]  D. Rubin,et al.  Statistical Analysis with Missing Data. , 1989 .

[8]  R. Bloch,et al.  Interobserver agreement for the assessment of handicap in stroke patients. , 1988, Stroke.

[9]  Nancy L. Geller,et al.  An approximate likelihood ratio test for a normal mean vector with nonnegative components with application to clinical trials , 1989 .

[10]  G Wassmer,et al.  Procedures for two-sample comparisons with multiple endpoints controlling the experimentwise error rate. , 1991, Biometrics.

[11]  D I Tang,et al.  On the design and analysis of randomized clinical trials with multiple endpoints. , 1993, Biometrics.

[12]  L Hothorn,et al.  Multiple comparisons in long-term toxicity studies. , 1994, Environmental health perspectives.

[13]  S. Medendorp,et al.  Low‐dose (7.5 mg) oral methotrexate reduces the rate of progression in chronic progressive multiple sclerosis , 1995, Annals of neurology.

[14]  R Little,et al.  Intent-to-treat analysis for longitudinal studies with drop-outs. , 1996, Biometrics.

[15]  N L Geller,et al.  Use of a global test for multiple outcomes in stroke trials with application to the National Institute of Neurological Disorders and Stroke t-PA Stroke Trial. , 1996, Stroke.

[16]  Dei-In Tang,et al.  An Approximate Likelihood Ratio Test for Comparing Several Treatments to a Control , 1997 .

[17]  F. Samejima.  Graded Response Model , 1997 .

[18]  S. Pocock.  Clinical trials with multiple outcomes: a statistical perspective on their design, analysis, and interpretation. , 1997, Controlled clinical trials.

[19]  S. Janson,et al.  Clinical differences among women with and without self-reported perimenstrual asthma. , 1998, Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology.

[20]  I. Shoulson.  DATATOP: a decade of neuroprotective inquiry. Parkinson Study Group. Deprenyl And Tocopherol Antioxidative Therapy Of Parkinsonism. , 1998, Annals of neurology.

[21]  Ira Shoulson,et al.  DATATOP: A decade of neuroprotective inquiry , 1998 .

[22]  D I Tang,et al.  Closed Testing Procedures for Group Sequential Clinical Trials with Multiple Endpoints , 1999, Biometrics.

[23]  M. Lezak,et al.  Neuropsychological impairment in amateur soccer players. , 1999, JAMA.

[24]  C Trenkwalder,et al.  A randomized controlled study of pergolide in patients with restless legs syndrome , 1999, Neurology.

[25]  Joseph P. Broderick,et al.  Effects of tissue plasminogen activator for acute ischemic stroke at one year , 1999 .

[26]  J. Douglas.  Item response models for longitudinal quality of life data in clinical trials. , 1999, Statistics in medicine.

[27]  M. van Kleef,et al.  Randomized trial of radiofrequency lumbar facet denervation for chronic low back pain. , 1999, Spine.

[28]  David E. Booth,et al.  Analysis of Incomplete Multivariate Data , 2000, Technometrics.

[29]  Andrew Thomas,et al.  WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility , 2000, Stat. Comput..

[30]  D. Li,et al.  Randomized controlled trial of interferon-beta-1a in secondary progressive MS: MRI results , 2001 .

[31]  H. Glick,et al.  Preference-based quality-of-life in patients with Parkinson’s disease , 2002, Neurology.

[32]  Bhushan Kumar,et al.  Minoxidil vs finasteride in the treatment of men with androgenetic alopecia. , 2003, Archives of dermatology.

[33]  Nicole A. Lazar,et al.  Statistical Analysis With Missing Data , 2003, Technometrics.

[34]  T. Karrison,et al.  A Rank-Sum-Type Test for Paired Data with Multiple Endpoints , 2004 .

[35]  Garrett M. Fitzmaurice,et al.  Analysis of longitudinal multiple‐source binary data using generalized estimating equations , 2004 .

[36]  Mona L. Martin,et al.  Quality of life and parkinson's disease: Translation and validation of the US Parkinson's Disease Questionnaire (PDQ-39) , 1999, Quality of Life Research.

[37]  Anja Vogler,et al.  An Introduction to Multivariate Statistical Analysis , 2004 .

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

[39]  D. Andrade,et al.  Item response theory for longitudinal data: population parameter estimation , 2005 .

[40]  Stuart Lipsitz,et al.  Adjusting O'Brien's Test to Control Type I Error for the Generalized Nonparametric Behrens–Fisher Problem , 2005, Biometrics.

[41]  Houeto Jean-Luc.  [Parkinson's disease]. , 2022, La Revue du praticien.

[42]  Stan Lipovetsky,et al.  Generalized Latent Variable Modeling: Multilevel,Longitudinal, and Structural Equation Models , 2005, Technometrics.

[43]  D. Andrade,et al.  Item response theory for longitudinal data: Item and population ability parameters estimation , 2006 .

[44]  H. Earl,et al.  Epirubicin and cyclophosphamide, methotrexate, and fluorouracil as adjuvant therapy for early breast cancer. , 2006, The New England journal of medicine.

[45]  J. Verkuilen.  Explanatory Item Response Models: A Generalized Linear and Nonlinear Approach by P. de Boeck and M. Wilson and Generalized Latent Variable Modeling: Multilevel, Longitudinal and Structural Equation Models by A. Skrondal and S. Rabe-Hesketh , 2006, Psychometrika.

[46]  Ninds Net-Pd Investigators.  A randomized, double-blind, futility clinical trial of creatine and minocycline in early Parkinson disease. , 2006 .

[47]  R. Elble,et al.  A randomized, double-blind, futility clinical trial of creatine and minocycline in early Parkinson disease , 2006, Neurology.

[48]  David B Dunson,et al.  Bayesian methods for latent trait modelling of longitudinal data , 2007, Statistical methods in medical research.

[49]  J. Jankovic,et al.  A randomized clinical trial of coenzyme Q10 and GPI-1485 in early Parkinson disease , 2007, Neurology.

[50]  Peng Huang,et al.  The Use of a Global Statistical Approach for the Design and Data Analysis of Clinical Trials with Multiple Primary Outcomes , 2008 .

[51]  Peng Huang,et al.  A rank‐based sample size method for multiple outcomes in clinical trials , 2008, Statistics in medicine.

[52]  Joseph G. Ibrahim,et al.  Missing data methods in longitudinal studies: a review , 2009 .

[53]  Chunling Liu,et al.  A Rank-Based Test for Comparison of Multidimensional Outcomes , 2010, Journal of the American Statistical Association.

[54]  Jean-Paul Fox,et al.  Bayesian Item Response Modeling , 2010 .

[55]  John K Kruschke,et al.  Bayesian data analysis. , 2010, Wiley interdisciplinary reviews. Cognitive science.

[56]  J. Fox.  Bayesian Item Response Modeling: Theory and Applications , 2010 .

[57]  Gary King,et al.  Amelia II: A Program for Missing Data , 2011 .

[58]  Martyn Plummer,et al.  JAGS Version 3.3.0 user manual , 2012 .

[59]  P. O'Brien,et al.  Global Assessment Variables , 2014 .

[60]  Lena Osterhagen,et al.  Multiple Imputation For Nonresponse In Surveys , 2016 .

[61]  Marie Schmidt,et al.  Nonparametrics Statistical Methods Based On Ranks , 2016 .