Cited by 913Statistical Methods and Bayesian InferenceAdvanced Causal Inference TechniquesStatistical Methods in Clinical Trials

The DOI matches its Crossref record.

Multiple Imputation and its Application

Carpenter, James R., Kenward, Michael G.·2013·Wiley eBooks

DOI 10.1002/9781119942283

Open this paper in CoChat — free account

Abstract

A practical guide to analysing partially observed data. Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods. This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures. Multiple Imputation and its Application: Discusses the issues raised by the analysis of partially observed data, and the assumptions on which analyses rest. Presents a practical guide to the issues to consider when analysing incomplete data from both observational studies and randomized trials. Provides a detailed discussion of the practical use of MI with real-world examples drawn from medical and social statistics. Explores handling non-linear relationships and interactions with multiple imputation, survival analysis, multilevel multiple imputation, sensitivity analysis via multiple imputation, using non-response weights with multiple imputation and doubly robust multiple imputation. Multiple Imputation and its Application is aimed at quantitative researchers and students in the medical and social sciences with the aim of clarifying the issues raised by the analysis of incomplete data data, outlining the rationale for MI and describing how to consider and address the issues that arise in its application.

Integrity signals

Registry

Crossref · 10.1002/9781119942283

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Sorted by citations

Items 601–700 of 911

Multiple imputation approaches for handling incomplete three‐level data with time‐varying cluster‐memberships
Wijesuriya, R., Moreno‐Betancur, M., Carlin, J. B., Silva, A. P. D., & Lee, K. J. (2022) · Statistics in Medicine · doi:10.1002/sim.9515 · Cited by 3
Robustness of Multiple Imputation Methods for Missing Risk Factor Data from Electronic Medical Records for Observational Studies
Paul, S. K., Ling, J. Z. J., Samanta, M., & Montvida, O. (2022) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-022-00119-w · Cited by 6
Gender inequality and utilization of ART: an international cross-sectional and longitudinal analysis.
Fitzgerald, O., Dyer, S., Zegers-Hochschild, F., Keller, E., Adamson, G., & Chambers, G. (2023) · Human Reproduction · doi:10.1093/humrep/dead225 · Cited by 2
Combining randomized and non‐randomized data to predict heterogeneous effects of competing treatments
Chalkou, K., Hamza, T., Benkert, P., Kühle, J., Zecca, C., Simoneau, G., Pellegrini, F., Manca, A., Egger, M., & Salanti, G. (2024) · Research Synthesis Methods · doi:10.1002/jrsm.1717 · Cited by 5
Adjusting for Baseline on the Analysis of Repeated Binary Responses With Missing Data
Jiang, H. H., Kulkarni, P. M., Mallinckrodt, C. H., et al. (2015) · Statistics in Biopharmaceutical Research · doi:10.1080/19466315.2015.1067251 · Cited by 5
“Multiple imputation (MI) approaches (Rubin 1987; Schafer 1999; Shieh 2003; Li et al. 2006; Carpenter and Kenward 2013; van Buuren 2014) are commonly applied to continuous incomplete longitudinal data and can therefore be used to impute the continuous outcome from which the binary responses are…”
Background
Missing data in clinical research: an integrated approach
Hollestein, L. M., & Carpenter, J. R. (2017) · British Journal of Dermatology · doi:10.1111/bjd.16010 · Cited by 5
Self-citation
Does pattern mixture modelling reduce bias due to informative attrition compared to fitting a mixed effects model to the available cases or data imputed using multiple imputation?: a simulation study
Welch, C. A., Sabia, S., Brunner, E. J., Mika Kivimaki, B., & Shipley, M. J. (2018) · BMC Medical Research Methodology · doi:10.1186/s12874-018-0548-0 · Cited by 5
Modelling cancer outcomes of bone metastatic patients: combining survival data with N-Telopeptide of type I collagen (NTX) dynamics through joint models
Loureiro, H., Carrasquinha, E., Alho, I., et al. (2019) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-018-0728-1 · Cited by 5
Analysis of Hierarchical Routine Data With Covariate Missingness: Effects of Audit & Feedback on Clinicians' Prescribed Pediatric Pneumonia Care in Kenyan Hospitals
Gachau, S., Onyango, N. O., Njagi, E. N., Ayieko, P., & English, M. (2019) · Frontiers in Public Health · doi:10.3389/fpubh.2019.00198 · Cited by 5
Missing Data
Tong, G., Li, F., & Allen, A. S. (2019) · Springer eBooks · doi:10.1007/978-3-319-52677-5_117-1 · Cited by 5
Descriptive Statistics
Mooi, E., Sarstedt, M., & Mooi‐Reci, I. (2017) · Springer texts in business and economics · doi:10.1007/978-981-10-5218-7_5 · Cited by 5
Missing Data in Meta-Analysis
Schwarzer, G., Carpenter, J. R., & Rücker, G. (2015) · Use R! · doi:10.1007/978-3-319-21416-0_6 · Cited by 5
Self-citation
Missing Data Analysis in Practice
Tanna, G. L. D. (2017) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12263 · Cited by 5
Analyses under Missing‐not‐at‐random Assumptions
O’Kelly, M., & Ratitch, B. (2014) · doi:10.1002/9781118762516.ch7 · Cited by 5
Bayesian Statistical Economic Evaluation Methods for Health Technology Assessment
Gabrio, A., Baio, G., & Manca, A. (2019) · Oxford Research Encyclopedia of Economics and Finance · doi:10.1093/acrefore/9780190625979.013.451 · Cited by 4
A data driven approach to address missing data in the 1970 British birth cohortPreprint
Katsoulis, M., Narayanan, M. K., Dodgeon, B., Ploubidis, G. B., & Silverwood, R. J. (2024) · medRxiv · doi:10.1101/2024.02.01.24302101 · Cited by 5
Quality Control, Data Cleaning, Imputation
Liu, D., Oberman, H., Muñoz, J., Hoogland, J., & Debray, T. P. A. (2023) · Springer eBooks · doi:10.1007/978-3-031-36678-9_2 · Cited by 12
The performance of a Bayesian value-based sequential clinical trial design in the presence of an equivocal cost-effectiveness signal: evidence from the HERO trial
Welch, C., Förster, M., Ronaldson, S. J., Keding, A., Corbacho, B., & Tharmanathan, P. (2024) · BMC Medical Research Methodology · doi:10.1186/s12874-024-02248-9 · Cited by 4
Multiple imputation of partially observed covariates in discrete-time survival analysis
Haensch, A., Bartlett, J. W., & Weiß, B. (2022) · Sociological Methods & Research · doi:10.1177/00491241221140147 · Cited by 4
“One consequence of this approach is a possibly considerable loss of ef ﬁ ciency or information (Carpenter and Kenward, 2013: 9) as only the observations with complete records are used.”
Influential
Quality of life with docetaxel plus cisplatin versus paclitaxel plus carboplatin in patients with completely resected non-small cell lung cancer: quality of life analysis of TORG 0503
Matsuda, A., Yamaoka, K., Kunitoh, H., Seto, T., Tsuboi, M., Ohira, T., Maruyama, R., Okamoto, H., & Kubota, K. (2023) · Quality of Life Research · doi:10.1007/s11136-023-03424-y · Cited by 6
“The multiple imputation (MI) method [17, 18] and the simple imputation (SI) method were used to manage missing data.”
Method
The relationship between mindfulness facets, self-compassion, and aggression in young adult women
Fuchs, D. E., Fleischmann, M. H., Wisener, M., & Khoury, B. (2023) · Current Psychology · doi:10.1007/s12144-023-04732-9 · Cited by 4
Injury outcomes across Canadian trauma systems: a historical cohort study
Moore, L., Thakore, J., Evans, D., et al. (2023) · Canadian Journal of Anesthesia/Journal canadien d anesthésie · doi:10.1007/s12630-023-02522-2 · Cited by 4
“We used the Markov Chain Monte Carlo method with single chains based on a multivariate normal model to generate 25 imputations, corresponding to the highest fraction of missing data.(19)”
Methods for handling missing binary data in substance use disorder trials
Ren, B., Lipsitz, S. R., Weiss, R. D., et al. (2023) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2023.110897 · Cited by 4
Childhood and adolescence factors and multiple sclerosis: results from the German National Cohort (NAKO)
Holz, A., Obi, N., Ahrens, W., Berger, K., Bohn, B., Brenner, H., Fischer, B., Fricke, J., Führer, A., Gastell, S., et al. (2024) · BMC Neurology · doi:10.1186/s12883-024-03620-4 · Cited by 8
Handling incomplete correlated continuous and binary outcomes in meta‐analysis of individual participant data
Gomes, M., Hatfield, L. A., & Normand, S. T. (2016) · Statistics in Medicine · doi:10.1002/sim.6969 · Cited by 3
Multiple imputation for gamma outcome variable using generalized linear model
Gupta, V. K., & Grover, G. (2017) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2017.1300904 · Cited by 4
Comparison of multiple imputation and two-phase logistic regression to analyse two-phase case–control studies with rich phase 1: a simulation study
Enders, D., Kollhorst, B., Engel, S., et al. (2018) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2018.1452926 · Cited by 4
Early ultrasonographic tumor regression after linear accelerator stereotactic fractionated photon radiotherapy of choroidal melanoma as a predictor for metastatic spread
Mitsch, C., Zehetmayer, M., Gleiß, A., et al. (2018) · Radiotherapy and Oncology · doi:10.1016/j.radonc.2018.04.019 · Cited by 4
¿Cómo se modificarían la pobreza y la desigualdad de ingresos de los hogares si se cierran las brechas de género en el mercado laboral? Un estudio para cuatro países de América Latina
Colacce, M. (2018) · Revista Desarrollo y Sociedad · doi:10.13043/dys.81.1 · Cited by 4
Propensity scores for proxy reports of care experience and quality: are they useful?
Roydhouse, J., Gutman, R., Keating, N., Mor, V., & Wilson, I. (2019) · Health Services & Outcomes Research Methodology · doi:10.1007/s10742-019-00205-4 · Cited by 3
Estimating adjusted risk differences by multiply‐imputing missing control binary potential outcomes following propensity score‐matching
Austin, P. C., Rubin, D. B., & Thomas, N. (2021) · Statistics in Medicine · doi:10.1002/sim.9141 · Cited by 4
Being Left Alone at Home and Dental Caries of Children Aged 6–7 Years
Matsuyama, Y., Isumi, A., Doi, S. K., & Fujiwara, T. (2021) · Journal of Epidemiology · doi:10.2188/jea.je20210321 · Cited by 4
Deep brain stimulation for dystonia
Duarte, G. S., Rodrigues, F. B., Prescott, D. F., Ferreira, J. J., & Costa, J. N. (2016) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd012405 · Cited by 4
Missing Step Count Data? Step Away From the Expectation–Maximization Algorithm
Tackney, M. S., Stahl, D. R., Williamson, E., & Carpenter, J. R. (2022) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2022-0002 · Cited by 4
“We describe the joint modeling approach here, though the alternative method of full conditional specification, also known as imputation using chained equations, can be taken (Carpenter & Kenward, 2012, p. 85).”
MethodSelf-citation
Handling Missing Data in Structural Equation Models in R. A Replication Study for Applied Researchers
Wolgast, A., Schwinger, M., Hahnel, C., et al. (2017) · Electronic Journal of Research in Educational Psychology · doi:10.25115/ejrep.41.16125 · Cited by 4
Combining Factors from Different Factor Analyses Based on Factor Congruence
Lovik, A., Nassiri, V., Verbeke, G. N., et al. (2018) · Springer proceedings in mathematics & statistics · doi:10.1007/978-3-319-77249-3_18 · Cited by 4
Do private school girls marry rich?
Green, F., Parsons, S., Sullivan, A., et al. (2018) · Longitudinal and Life Course Studies · doi:10.14301/llcs.v9i3.496 · Cited by 4
Handling missing data in a composite outcome with partially observed components: simulation study based on clustered paediatric routine data
Gachau, S., Njagi, E. N., Owuor, N. O., Mwaniki, P., Quartagno, M., Sarguta, R. J., English, M., & Ayieko, P. (2021) · Journal of Applied Statistics · doi:10.1080/02664763.2021.1895087 · Cited by 4
Quality of life in bariatric patients up to twelve years after surgery – Results from a nationwide retrospective cohort study
Riedel, O., Braitmaier, M., Dankhoff, M., Hornschuch, M., Klein, M., Zachariassen, W., & Hoyer, J. (2023) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2023.08.001 · Cited by 5
Spatial smoothing models to deal with the complex sampling design and nonresponse in the Florida BRFSS survey
Watjou, K., Faes, C., Kirby, R. S., Aregay, M., Carroll, R. M., & Vandendijck, Y. (2019) · Spatial and Spatio-temporal Epidemiology · doi:10.1016/j.sste.2019.03.001 · Cited by 4
Addressing missing data in patient-reported outcome measures (PROMs): implications for comparing provider performancePreprint
Gomes, M., Gutacker, N., Bojke, C., et al. (2014) · RePEc: Research Papers in Economics · Cited by 4
Poverty Imputation in Contexts without Consumption Data: A Revisit with Further Refinements
Kilic, T., Dang, H.-A. H., Carletto, C., et al. (2021) · World Bank, Washington, DC eBooks · doi:10.1596/1813-9450-9838 · Cited by 4
Meta-Analyzing Individual Participant Data From Studies With Complex Survey Designs: A Tutorial on Using the Two-Stage Approach for Data From Educational Large-Scale AssessmentsPreprint
Brunner, M., Keller, L., Stallasch, S. E., Kretschmann, J., Hasl, A., Preckel, F., Lüdtke, O., & Hedges, L. V. (2021) · doi:10.31234/osf.io/t79vk · Cited by 4
Handling of missing component information for common composite score outcomes used in axial spondyloarthritis research when complete-case analysis is unbiased
Polysopoulos, C., Georgiadis, S., Ørnbjerg, L. M., et al. (2025) · BMC Medical Research Methodology · doi:10.1186/s12874-025-02515-3 · Cited by 3
Early Risk Prediction in Acute Aortic Syndrome on Clinical Data Using Machine Learning
Tavafi, M., Passi, K., & Ohle, R. (2025) · Algorithms · doi:10.3390/a18050257 · Cited by 3
Unilateral upper lung field pulmonary fibrosis after primary lung cancer surgery as a late complication to be recognized
Ishibashi, H., Hanafusa, M., Asakawa, A., et al. (2025) · General Thoracic and Cardiovascular Surgery · doi:10.1007/s11748-025-02164-9 · Cited by 3
Sensitivity Analyses for Missing in Repeatedly Measured Outcome Data
Troendle, J. F., Sur, A., Leifer, E., & Powell‐Wiley, T. M. (2025) · Statistics in Medicine · doi:10.1002/sim.70282 · Cited by 3
A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting
Zahra, A., Luijken, K., Abbink, E. J., van den Berg, J. M., Blom, M. T., Elders, P. J. M., Festen, J., Gussekloo, J., Joling, K. J., Melis, R. J. F., et al. (2023) · Diagnostic and Prognostic Research · doi:10.1186/s41512-023-00144-2 · Cited by 3
Net survival in colon and rectal cancer by stage according to neoadjuvant treatment. A French population-based study
Jooste, V., Grosclaude, P., Défossez, G., Daubisse‐Marliac, L., Woronoff, A., Bouvier, V., Chirpaz, E., Trétarre, B., Lapôtre‐Ledoux, B., Plouvier, S., et al. (2023) · Digestive and Liver Disease · doi:10.1016/j.dld.2023.10.012 · Cited by 3
Using linked administrative data to aid the handling of non-response and restore sample representativeness in cohort studies: the 1958 national child development study and hospital episode statistics data
Rajah, N., Calderwood, L., Stavola, B. L. D., Harron, K. L., Ploubidis, G. B., & Silverwood, R. J. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-023-02099-w · Cited by 3
“Recent decades have seen the establishment of a number of principled methods for the handling of missing data, such as multiple imputation (MI) [3], full information maximum likelihood (FIML) [4] and inverse probability weighting (IPW) [5].”
Sense of relatedness and science engagement among Filipino high school students
Datu, J. A. D., & Noltemeyer, A. L. (2024) · Psychology in the Schools · doi:10.1002/pits.23224 · Cited by 9
Individual and familial factors associated with mRNA COVID-19 vaccine uptake in pregnancy: A large-scale registry-based linkage study
Elyass, J., Desalegn, A. A., Trinh, N. T., et al. (2024) · Vaccine · doi:10.1016/j.vaccine.2024.126171 · Cited by 3
Successful Medial Meniscal Repair Reduces Knee Pain 10 Years After Anterior Cruciate Ligament Reconstruction: Exploring the Consequences of Subsequent Surgery With Causal Mediation Analysis in the MOON Cohort
Sheean, A. J., Jin, Y., Amendola, A., et al. (2025) · The American Journal of Sports Medicine · doi:10.1177/03635465251317742 · Cited by 3
Multilevel multiple imputation: An examination of competing methods
Mistler, S. A. (2015) · Cited by 3
Harnessing paradata and multilevel multiple imputation when analysing survey data: a case study
Brunton‐Smith, I., & Tarling, R. (2017) · International Journal of Social Research Methodology · doi:10.1080/13645579.2017.1287842 · Cited by 3
“Although it is outside the remit of this paper to describe MI and its theoretical underpinnings in detail (see Carpenter & Kenward, 2013; Lee et al., 2016), for ease of reference, we briefly outline the steps of MI.”
Method
Investigating the inequalities in route to diagnosis amongst patients with diffuse large B-cell or follicular lymphoma in England
Smith, M. J., Luque-Fernández, M. Á., Belot, A., Quartagno, M., Bonaventure, A., Majano, S. B., Rachet, B., & Njagi, E. N. (2021) · British Journal of Cancer · doi:10.1038/s41416-021-01523-6 · Cited by 3
Dealing with missing information on covariates for excess mortality hazard regression models – Making the imputation model compatible with the substantive model
Antunes, L., Mendonça, D. M., Bento, M. J., et al. (2021) · Statistical Methods in Medical Research · doi:10.1177/09622802211031615 · Cited by 3
Survey Research in Times of Big Data
Cabrera‐Álvarez, P. (2022) · Empiria Revista de metodología de ciencias sociales · doi:10.5944/empiria.53.2022.32611 · Cited by 3
Missing Data
Tong, G., Li, F., & Allen, A. S. (2022) · Springer eBooks · doi:10.1007/978-3-319-52636-2_117 · Cited by 3
Using the multiphase optimization strategy to adapt cognitive processing therapy (CPT MOST): study protocol for a randomized controlled factorial experiment
Sripada, R. K., Peterson, C. L., Dziak, J. J., Nahum-Shani, I. B., Roberge, E. M., Martinson, A. A., Porter, K. E., Grau, P. P., Curtis, D., McElroy, S., et al. (2023) · Trials · doi:10.1186/s13063-023-07669-3 · Cited by 4
“…if missingness is greater than 10%, we will also conduct sensitivity analysis with multiple imputation procedures implemented with chained equations to determine whether results are consistent under different missing-ness assumptions such as missingness depending on baseline symptom severity [65].”
Method
On the use of multiple imputation to address data missing by design as well as unintended missing data in case-cohort studies with a binary endpoint
Middleton, M., Nguyen, C. D., Carlin, J. B., Moreno‐Betancur, M., & Lee, K. J. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-023-02090-5 · Cited by 3
Musculoskeletal Health and Work: Development and Internal–External Cross-Validation of a Model to Predict Risk of Work Absence and Presenteeism in People Seeking Primary Healthcare
Archer, L., Peat, G., Snell, K. I. E., Hill, J. C., Dunn, K. M., Foster, N. E., Bishop, A., van der Windt, D., & Wynne‐Jones, G. (2024) · Journal of Occupational Rehabilitation · doi:10.1007/s10926-024-10223-w · Cited by 4
Not all Christian nationalists are White (and not all White Christians are Christian nationalists): exploring the predictors of Christian nationalism
Everton, S. F. (2024) · Frontiers in Social Psychology · doi:10.3389/frsps.2024.1465810 · Cited by 6
Selbstständigkeit von Bilanzbuchhaltern und Controllern: Eine empirische Untersuchung zu Einkommen und Determinanten
Rieg, R. (2019) · Zeitschrift für Klein- und Mittelunternehmen/Zeitschrift für KMU und Entrepreneurship · doi:10.3790/zfke.67.1.35 · Cited by 3
Information anchored reference‐based sensitivity analysis for truncated normal data with application to survival analysis
Atkinson, A., Cro, S., Carpenter, J. R., & Kenward, M. G. (2021) · Statistica Neerlandica · doi:10.1111/stan.12250 · Cited by 3
“…MI is formally Bayesian, we assume the observed data dominates the posterior distribution, and, using inferential arguments set out on pp. 56–60 of Carpenter and Kenward (2013), we can, without any important loss of generality, assume the variance of the data is known in the imputation model.”
MethodSelf-citation
Adapted Factor-Type Imputation Strategies
Pandey, R., Yadav, K., & Thakur, N. S. (2016) · Journal of Scientific Research · doi:10.3329/jsr.v8i3.27804 · Cited by 3
Impact of the non-distinctness and non-ignorability on the inference by multiple imputation in multivariate multilevel data: a simulation assessment
Yucel, R. M. (2017) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2017.1288233 · Cited by 3
Multiple Imputation by Chained Equation
Noma, H. (2017) · Ouyou toukeigaku · doi:10.5023/jappstat.46.67 · Cited by 2
Associations between school and neighbourhood ethnic density and physical activity in adolescents: Evidence from the Olympic Regeneration in East London (ORiEL) study
Berger, N., Lewis, D. J., Quartagno, M., et al. (2019) · Social Science & Medicine · doi:10.1016/j.socscimed.2019.112426 · Cited by 3
Missing Data Analyses
Baraldi, A. N., & Enders, C. K. (2020) · Cambridge University Press eBooks · doi:10.1017/9781316995808.040 · Cited by 4
A multiple regression imputation method with application to sensitivity analysis under intermittent missingness
Uranga, R., Molenberghs, G., & Allende, S. (2020) · Communication in Statistics- Theory and Methods · doi:10.1080/03610926.2020.1834581 · Cited by 3
“According to Carpenter and Kenward (2013), “Given a set of assumptions about the reasons data are missing, there are a number of statistical methods for carrying out the analysis.”
BackgroundMethodInfluential
Multiple Imputation
Ratitch, B. (2014) · doi:10.1002/9781118762516.ch6 · Cited by 3
Selection Model (Missing Data)
Little, R. J. A. (2016) · Wiley StatsRef: Statistics Reference Online · doi:10.1002/9781118445112.stat07871 · Cited by 3
Handling missing data in cross-classified multilevel analyses: An evaluation of different multiple imputation approachesPreprint
Grund, S., Lüdtke, O., & Robitzsch, A. (2022) · doi:10.31234/osf.io/sny45 · Cited by 3
Questionable Research Practices and Open Science in Quantitative CriminologyPreprint
Chin, J. M., Pickett, J. T., Vazire, S., & Holcombe, A. O. (2024) · CrimRxiv · doi:10.21428/cb6ab371.0d3ec44f · Cited by 3
The Association of Oxaliplatin-Containing Adjuvant Chemotherapy Duration with Overall and Cancer-Specific Mortality in Individuals with Stage III Colon Cancer: A Population-Based Retrospective Cohort Study
Sue‐Chue‐Lam, C., Brezden‐Masley, C., Sutradhar, R., Yu, A., & Baxter, N. N. (2023) · Current Oncology · doi:10.3390/curroncol30070478 · Cited by 2
Impact of a Web-Based Decision Aid on Socioeconomically Disadvantaged Patients’ Engagement in Breast Surgery Decision-Making: Stepped-Wedge Clinical Trial (Alliance-A231701CD)
Schumacher, J. R. M., Hanlon, B. M., Zahrieh, D. M., Rathouz, P. J., Tucholka, J. L., McKinney, G., Tan, A. D., Breuer, C. R., Bailey, L., Higham, A. M., et al. (2025) · Annals of Surgical Oncology · doi:10.1245/s10434-025-17452-0 · Cited by 2
Dynamics between tonic irritability, phasic irritability, and loneliness in adults: A daily diary study
Liu, Q., Nelson, N., Tran, T., Fulford, D., & Yung, A. (2025) · Personality and Individual Differences · doi:10.1016/j.paid.2025.113290 · Cited by 2
A new framework for multiple imputation and applications to a binary variable
Laaksonen, S. (2016) · Model Assisted Statistics and Applications · doi:10.3233/mas-160369 · Cited by 2
“This term, ‘non-Bayesian,’ is not really used in the imputation literature; it cannot be found six years later in a book by Carpenter and Kenward (2013) that closely follows Rubin’s framework.”
Protecting energy intakes against income shocks
von Hinke, S., & Leckie, G. (2017) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2017.06.007 · Cited by 3
Visual analysis for panel data imputation with Bayesian network
Yeon, H., Seo, S., Son, H., & Jang, Y. (2021) · The Journal of Supercomputing · doi:10.1007/s11227-021-03934-x · Cited by 2
Health system influences on potentially avoidable hospital admissions by secondary mental health service use: A national ecological study
Woodhead, C., Martin, P. J., Osborn, D., et al. (2021) · Journal of Health Services Research & Policy · doi:10.1177/13558196211036739 · Cited by 2
Imputation for sub-sampling in Indonesian National Socioeconomic Survey
Hasyyati, A. N., & Lumley, T. (2022) · Statistical Journal of the IAOS · doi:10.3233/sji-220085 · Cited by 2
Randomized controlled trial protocol of health coaching for veterans with complex chronic pain
Crosky, S., McFarlin, M. L., Sullivan, N. L., Winograd, D. M., Litke, D. R., Masheb, R. M., Lu, S., Costanzo, M. E., Anastasides, N., Gonzalez, C., et al. (2023) · Trials · doi:10.1186/s13063-023-07113-6 · Cited by 2
The Feasibility and Efficacy of a Group-Based, Brief Transdiagnostic Cognitive-Behavioral Treatment for Adolescents with Internalizing Problems
Skarphéðinsson, G., & Karlsson, G. K. (2023) · Child Psychiatry & Human Development · doi:10.1007/s10578-023-01552-7 · Cited by 7
“The imputation model [47, 48] included demographic, K-SADS diagnoses, all available outcome measures, and treatment indicator.”
Protocol for a cluster randomised waitlist-controlled trial of a goal-based behaviour change intervention for employees in workplaces enrolled in health and wellbeing initiatives
Alidu, L., Al-Khudairy, L., Bharatan, I., Bird, P., Campbell, N., Currie, G., Hemming, K., Jolly, K. B., Kudrna, L., Lilford, R. J., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0282848 · Cited by 3
Copula-based pairwise estimator for quantile regression with hierarchical missing data
Verhasselt, A., Flórez, A. J., Molenberghs, G., et al. (2024) · Statistical Modelling · doi:10.1177/1471082x231225806 · Cited by 2
Community-level group sports participation and all-cause, cardiovascular disease, and cancer mortality: a 7-year longitudinal study
Tsuji, T., Okada, E., Saito, M., et al. (2024) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-024-01592-9 · Cited by 2
A demonstration of estimands and sensitivity analyses for time-to-deterioration of patient reported outcomes
Floden, L. L., DeRosa, M., Roydhouse, J. K., et al. (2024) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2024.2341649 · Cited by 2
“Standard MI imputes missing responses under a MAR assumption (Carpenter and Kenward 2013).”
Influential
Missing Data in the Analysis of Multilevel and Dependent Data
Grund, S., Lüdtke, O., & Robitzsch, A. (2024) · Springer eBooks · doi:10.1007/978-3-031-56318-8_12 · Cited by 2
Two-stage multiple imputation with a longitudinal composite variable
Wang, X., Larson, M. G., & Liu, C. (2025) · BMC Medical Research Methodology · doi:10.1186/s12874-025-02555-9 · Cited by 2
Hierarchical imputation of categorical variables in the presence of systematically and sporadically missing data
Jolani, S. (2025) · Research Synthesis Methods · doi:10.1017/rsm.2025.10017 · Cited by 3
“Figures A1–A5 present the ﬁndings of binary outcome when the rate of systematically missing data was 30%.”
Optimizing Autologous Hematopoietic Stem Cell Transplantation for Multiple Myeloma: Early Step-Down Ward Versus HEPA-Filtered Rooms: A Practical Approach for Resource-Limited Settings
Kunacheewa, C., Niwatkittipon, S., Atakulreka, S., Donsakul, N., Kungwankiattichai, S., Karoopongse, E., Jianthanakanon, J., Sonsak, N., Vittayawacharin, P., Meeudompong, U., et al. (2025) · Transplantation and Cellular Therapy · doi:10.1016/j.jtct.2025.10.018 · Cited by 3
Improved methods for reducing translocation mortality and obtaining reliable population projections for reintroduction of the New Zealand Rifleman Acanthisitta chloris
Withers, S. J., Armstrong, D. P., Ward-Smith, T., Parsons, S. E., & Hauber, M. E. (2019) · Bird Conservation International · doi:10.1017/s0959270918000412 · Cited by 2
“Consequently, the unknown age classes were modelled as missing values (Carpenter and Kenward 2013).”
A new robust ratio estimator by modified Cook’s distance for missing data imputation
Takahashi, M. (2022) · Japanese Journal of Statistics and Data Science · doi:10.1007/s42081-022-00164-0 · Cited by 2
Analysis and Visualization of Missing Value Patterns
van Stein, B., Kowalczyk, W., & Bäck, T. (2016) · Communications in computer and information science · doi:10.1007/978-3-319-40581-0_16 · Cited by 2
A review of the reporting and implementation of multiple imputation in medical research
Rezvan, P. H., Lee, K. J., & Simpson, J. A. (2015) · Cited by 2
Imputation methods for estimating public R&D funding: evidence from longitudinal data
Zinilli, A. (2020) · Quality & Quantity · doi:10.1007/s11135-020-01023-4 · Cited by 2
Childhood Mistreatment, PTSD, and Substance Use in Latinx: The Role of Discrimination in an Omitted-Variable Bias
Ai, A. L., Petscher, Y., Lemieux, C. M., Petscher, E. S., Clark, J. J., & Pappas, A. (2021) · International Journal of Behavioral Medicine · doi:10.1007/s12529-021-09954-4 · Cited by 2
Heterogeneity in the association between youth unemployment and mental health later in life: a quantile regression analysis of longitudinal data from English schoolchildren
Wright, L., Head, J. A., & Jivraj, S. (2021) · BMJ Open · doi:10.1136/bmjopen-2020-047997 · Cited by 2

Authors: Carpenter, J. R., & Kenward, M. G.
ORCID: Carpenter, James R.
Venue: Wiley eBooks
Publisher: Wiley
Published: 2012-12-18
DOI: 10.1002/9781119942283
OpenAlex: W1500944114
Cited by: 913
References: 0
Citations by year: 2026: 13 · 2025: 37 · 2024: 53 · 2023: 65 · 2022: 81 · 2021: 101 · 2020: 94 · 2019: 90 · 2018: 93 · 2017: 85 · 2016: 85 · 2015: 54 · 2014: 44 · 2013: 14 · 2012: 3
FWCI: 9.44
Type: book
Language: en
Open access: closed
Licence: doi.wiley.com/10.1002/tdm_license_1.1 (tdm)
Locations: Wiley eBooks (publishedVersion)
CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
LSHTM Research Online (London School of Hygiene and Tropical Medicine) (submittedVersion)
Wiley eBooks
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords: multiple imputation, missing data, incomplete data analysis, imputation models, observational studies, nonlinear relationship, survival analysis, sensitivity analysis, medical statistics, social statistics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Multiple Imputation and its Application

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cited by

Related

Metadata

Record

About these checks