Cited by 398Statistical Methods and Bayesian InferenceStatistical Methods in Clinical TrialsAdvanced Causal Inference Techniques

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

ACCOUNTING FOR DROPOUT BIAS USING MIXED-EFFECTS MODELS

Mallinckrodt, Craig H., Clark, W. Scott, David, Stacy R.·2001·Journal of Biopharmaceutical Statistics

DOI 10.1081/bip-100104194

Open this paper in CoChat — free account

Abstract

Treatment effects are often evaluated by comparing change over time in outcome measures. However, valid analyses of longitudinal data can be problematic when subjects discontinue (dropout) prior to completing the study. This study assessed the merits of likelihood-based repeated measures analyses (MMRM) compared with fixed-effects analysis of variance where missing values were imputed using the last observation carried forward approach (LOCF) in accounting for dropout bias. Comparisons were made in simulated data and in data from a randomized clinical trial. Subject dropout was introduced in the simulated data to generate ignorable and nonignorable missingness. Estimates of treatment group differences in mean change from baseline to endpoint from MMRM were, on average, markedly closer to the true value than estimates from LOCF in every scenario simulated. Standard errors and confidence intervals from MMRM accurately reflected the uncertainty of the estimates, whereas standard errors and confidence intervals from LOCF underestimated uncertainty.

Integrity signals

Registry

Crossref · 10.1081/bip-100104194

Cites

14 of 14 references verified0 citation errors · 0 not checkable

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?

SAS System for Mixed Models
Littell, R. C. (1996) · Medical Entomology and Zoology · Cited by 10,345
Linear Mixed Models for Longitudinal Data
Verbeke, G. (1997) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-2294-1_3 · Cited by 3,506
Linear Mixed Models for Longitudinal Data
Molenberghs, G., & Verbeke, G. N. (2000) · Springer series in statistics · doi:10.1007/978-1-4419-0300-6 · Cited by 2,681
Multiple imputation in health‐are databases: An overview and some applications
Rubin, D. B., & Nathaniel Schenker, A. (1991) · Statistics in Medicine · doi:10.1002/sim.4780100410 · Cited by 1,553
Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data
Cnaan, A., Laird, N. M., & Slasor, P. (1997) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(19971030)16:20 · Cited by 1,227
Olanzapine versus haloperidol in the treatment of schizophrenia and schizoaffective and schizophreniform disorders: results of an international collaborative trial
Tollefson, G. D., Beasley, C. M., Tran, P. V., Street, J. S., Krueger, J. A., Tamura, R., Graffeo, K. A., & Thieme, M. E. (1997) · American Journal of Psychiatry · doi:10.1176/ajp.154.4.457 · Cited by 891
Some Conceptual and Statistical Issues in Analysis of Longitudinal Psychiatric Data
Gibbons, R. D. (1993) · Archives of General Psychiatry · doi:10.1001/archpsyc.1993.01820210073009 · Cited by 719
Missing data in longitudinal studies
Laird, N. M. (1988) · Statistics in Medicine · doi:10.1002/sim.4780070131 · Cited by 713
A multiple imputation strategy for clinical trials with truncation of patient data
Lavori, P. W., Dawson, R., & Shera, D. M. (1995) · Statistics in Medicine · doi:10.1002/sim.4780141707 · Cited by 291
Statistical handling of drop‐outs in longitudinal clinical trials
Heyting, A., Tolboom, J. T. B. M., & Essers, J. G. A. (1992) · Statistics in Medicine · doi:10.1002/sim.4780111603 · Cited by 236

Flagged first, then by citations

Show all 14 references

Research works printed but not linked: 6

Milliken G. A., 1992, Designed Experiments, 326
Little T., 1987, Analysis with Missing Data
Lavori P. W., 1992, Neuropsychopharmacol, 6, 39
Kay S. R., 1986, Positive and Negative Syndrome Scale (PANSS) Manual
Mallinckrodt C. H., 1993, The Effects of Animal Model Approximations and Data Problems on the Reliability of Genetic Evaluations, Ph.D. Dissertation; Colorado State University: Fort Collins, CO
1997, SOLAS for Missing Data Analysis 1.0. Statistical Solutions Ltd: Cork

Sorted by citations

Items 301–398 of 398

Missing Data
Molenberghs, G., Beunckens, C., Jansen, I., Thijs, H., Verbeke, G. N., & Kenward, M. G. (2013) · Springer eBooks · doi:10.1007/978-0-387-09834-0_20 · Cited by 4
Statistical Evidence in Medical Trials: What Do the Data Really Tell Us?
Goldstein, R. B. (2007) · Technometrics · doi:10.1198/tech.2007.s463 · Cited by 4
“…observation carried forward (LOCF) method of imputing data (when the last observation for a subject is missing in a longitudinal study, LOCF would have the researcher copy the most recent actual measure as though it were unchanged) (Cook, Zeng, and Yi 2004; Mallinckrodt, Clark, and David 2001).”
Method
A RANDOMIZED, PLACEBO-CONTROLLED TRIAL OF REPEATED IV ANTIBIOTIC THERAPY FOR LYME ENCEPHALOPATHY PROLONGED LYME DISEASE TREATMENT: ENOUGH IS ENOUGH
Marques, A. R., Shaw, P. J., Schmid, C. H., Steere, A. C., Kaplan, R. F., Hassett, A. L., Shapiro, E. D., & Wormser, G. P. (2009) · Neurology · doi:10.1212/01.wnl.0000343855.45704.7c · Cited by 4
Multidomain interventions for preventing cognitive decline in older adults with type 2 diabetes and mild cognitive impairment: Secondary analysis of the J-MINT
Sugimoto, T., Crane, P. K., Choi, S., Fujita, K., Gallée, J., Kuroda, Y., Lee, M. K., Matsumoto, N., Nakamura, A., Noma, H., et al. (2025) · Journal of Aging Research and Lifestyle · doi:10.1016/j.jarlif.2025.100016 · Cited by 3
Differential effects of a multidomain intervention on cognitive decline in older adults with type 2 diabetes according to white matter hyperintensity status: A secondary analysis of the J‐ MIND ‐Diabetes
Sugimoto, T., Omura, T., Araki, A., Haneda, C., Honda, K., Kishi, M., Takahashi, T., Toyoshima, K., Tsuume, S., Uchida, K., et al. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16605 · Cited by 4
IDTWO: A Protocol for a Randomised Controlled Trial of a Web-Based Mental Health Intervention for Australians with Intellectual Disability
Baldwin, P. A., Rasmussen, V., Trollor, J. N., Zhao, J. L., Anderson, J., Christensen, H. M., & Boydell, K. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18052473 · Cited by 3
“Missing data will be handled using maximum-likelihood estimation within the MMRM procedure, as this appears to be more robust to violations of the assumption of randomness due to attrition [45].”
Method
Collaborative Care for Bipolar Disorder: Part II. Impact on Clinical Outcome, Function, and Costs
Bauer, M. S., McBride, L., Williford, W. O., Glick, H. A., Kinosian, B. P., Altshuler, L. L., Beresford, T. P., Kilbourne, A. M., Sajatovic, M., Coauthors for the Cooperative Studies Program 430 Study Team, et al. (2015) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.130114 · Cited by 3
Patient-controlled epidural analgesia, patient-controlled intravenous analgesia, and conventional intravenous opioids for gynecologic interstitial brachytherapy: A single-center retrospective study
Murata, Y., Yamada, K., Hamaguchi, Y., Ohigashi, T., Maruo, K., Yamashita, S., & Tanaka, M. (2021) · Brachytherapy · doi:10.1016/j.brachy.2021.03.006 · Cited by 3
Effectiveness of an online support program to help female cancer patients manage their health and illness: Protocol for a randomized controlled trial
Mizuno, M., Chiba, I., Mukohara, T., Kondo, M., Maruo, K., Ohigashi, T., Naruo, M., Asano, Y., Onishi, T., Tanabe, H., et al. (2022) · Contemporary Clinical Trials Communications · doi:10.1016/j.conctc.2022.101035 · Cited by 3
“To evaluate the mean treatment effect, we will conduct a mixed model for repeated measures (MMRM) analysis [36] to detect changes in the total QLI score from baseline to 6 months.”
Method
Introduction
Potkin, S. G. (2008) · Journal of Clinical Psychopharmacology · doi:10.1097/jcp.0b013e318168f758 · Cited by 3
Analysis of Longitudinal Outcome Data with Missing Values in Total Knee Arthroplasty
Kang, Y. G., Lee, J. T., Kang, J. Y., Kim, G. H., & Kim, T. K. (2015) · The Journal of Arthroplasty · doi:10.1016/j.arth.2015.06.067 · Cited by 3
Statistical considerations
Thomas, S., Koch, G. G., Rosenheck, R. A., & Davis, V. G. (2010) · Cambridge University Press eBooks · doi:10.1017/cbo9780511712265.003 · Cited by 3
Α Markov model for longitudinal studies with incomplete dichotomous outcomes
Efthimiou, O., Welton, N. J., Samara, M. T., Leucht, S., Salanti, G., & 4, O. B. O. G. W. P. (2016) · Pharmaceutical Statistics · doi:10.1002/pst.1794 · Cited by 3
Improved Decision-Making Confidence Using Item-Based Pharmacometric Model: Illustration with a Phase II Placebo-Controlled Trial
Llanos‐Paez, C., Ambery, C. L., Yang, S., Tabberer, M. M., Beerahee, M., Plan, E. L., & Karlsson, M. O. (2021) · The AAPS Journal · doi:10.1208/s12248-021-00600-1 · Cited by 3
Methods to improve the efficiency of confirmatory clinical trials
Boessen, R. (2013) · Utrecht University Repository (Utrecht University) · Cited by 3
Comparison of Patient-Reported Outcomes for Elranatamab in MagnetisMM-3 Versus Real-World Physician Choice of Therapy for Triple-Class Refractory Multiple Myeloma
Hébraud, B., Charalampous, C., Parrondo, R. D., Chhabra, S., Nagaraj, M., DiBonaventura, M., Duh, M. S., Bobbili, P. J., Wang, A., Frey-Koba, S., et al. (2026) · Clinical Lymphoma Myeloma & Leukemia · doi:10.1016/j.clml.2026.03.014 · Cited by 2
Slowing the curve: a single-arm meta-analysis of mFARS outcomes following omaveloxolone treatment in Friedreich ataxia
Ali, A., Cheema, W. A., Nisar, F., Reyaz, U., Saad, M., Talha, M., Sarfraz, S., Butt, A., Shamoon, M., Abdullah, A., et al. (2026) · BMJ Neurology Open · doi:10.1136/bmjno-2026-001670 · Cited by 2
“27 28 Third, the interpretation of results within the context of natural history data provides a clinically meaningful framework for understanding absolute mFARS changes.”
Influential
A BIBLIOGRAPHY ON VARIANCE COMPONENTS AN INTRODUCTION AND AN UPDATE: 1984-2002
Sahai, H., & Khurshid, A. (2005) · Cited by 2
Testing treatment effect in schizophrenia clinical trials with heavy patient dropout using latent class growth mixture models
Kong, F., & Chen, Y. (2016) · Pharmaceutical Statistics · doi:10.1002/pst.1750 · Cited by 2
Hierarchical and incomplete data
Verbeke, G. N., & Molenberghs, G. (2024) · Handbook of statistics · doi:10.1016/bs.host.2023.10.005 · Cited by 2
LONGITUDINAL AND INCOMPLETE CLINICAL STUDIES
Molenberghs, G., & Verbeke, G. N. (2009) · Journal of the Japanese Society of Computational Statistics · doi:10.5183/jjscs.22.1_1 · Cited by 2
Missing Data
Molenberghs, G., & Lesaffre, E. M. E. H. (2014) · doi:10.1002/9781118596005.ch42 · Cited by 2
RESiLIENT (Resilience Enhancement with Smartphone in LIving ENvironmenTs) Trial: The Statistical Analysis PlanPreprint
Noma, H., Furukawa, T. A., Tajika, A., Sakata, M., Luo, Y., Toyomoto, R., Horikoshi, M., Akechi, T., Kawakami, N., Nakayama, T., et al. (2024) · medRxiv · doi:10.1101/2024.03.16.24304261 · Cited by 2
RESiLIENT (Resilience Enhancement with Smartphone in LIving ENvironmenTs) Trial: The Statistical Analysis Plan for 1-year follow-up dataPreprint
Noma, H., Furukawa, T. A., Tajika, A., Toyomoto, R., Sakata, M., Luo, Y., Horikoshi, M., Akechi, T., Kawakami, N., Nakayama, T., et al. (2025) · medRxiv · doi:10.1101/2025.02.20.25322386 · Cited by 2
Mixed-effects Models for Repeated Measures in Longitudinal Data Analysis: An Introduction to Methodology, Theory, and Applications
Gosho, M., & Maruo, K. (2017) · Ouyou toukeigaku · doi:10.5023/jappstat.46.53 · Cited by 1
Performance of LTMLE in the Presence of Missing Data in Control-Matched Longitudinal Studies
Wang, S., Huang, Z., & Zhu, H. (2022) · Statistics in Biopharmaceutical Research · doi:10.1080/19466315.2022.2108136 · Cited by 1
“When analyzing continuous outcome measures, Mallinckrodt, Clark, and David (2001) refer to the model as MMRM. Specifically, the MMRM model considers time as a factor variable and treatment-by-time effects are considered as an unstructured interaction effect, which provides the direct estimates and…”
MethodInfluential
Bayesian Method of Borrowing Study-Level Historical Longitudinal Control Data for Mixed-Effects Models with Repeated Measures
Li, H., Jin, M., Chung, Y.-C., Zhong, S., & Wang, L. (2022) · Therapeutic Innovation & Regulatory Science · doi:10.1007/s43441-022-00449-2 · Cited by 1
Dietary Intervention Favorably Influences Physical Functioning: The Women’s Health Initiative Randomized Dietary Modification Trial
Chlebowski, R. T., Aragaki, A. K., Pan, K., Nelson, R. A., Barac, A., Manson, J. E., Stefanick, M. L., Ikramuddin, F. S., Johnson, K., Krok‐Schoen, J. L., et al. (2024) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2024.02.012 · Cited by 2
Small sample adjustment for inference without assuming orthogonality in a mixed model for repeated measures analysis
Maruo, K., Ishii, R., Yamaguchi, Y., Ohigashi, T., & Gosho, M. (2024) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2024.2420632 · Cited by 1
“In the MMRM analysis, the marginal mean of each treatment group at a specified time point is defined as a function of β under model (1), and then the inference on the difference of marginal means between treatment groups is usually focused on (Mallinckrodt et al. 2001).”
The feasibility of salivary melatonin in assessing perioperative circadian rhythm in surgical patients: study protocol for a multicentre prospective study in China
Chen, B., Yuan, S., Wei, P., Jing, F., Zhu, M., Zhang, X., Zhang, Y., Zhang, Y., Wang, H., Su, Z., et al. (2025) · BMJ Open · doi:10.1136/bmjopen-2025-105679 · Cited by 1
“48 However, this study protocol has several limitations.”
Platform trial of smartphone-based cognitive–behavioural therapy (CBT) for depressive symptoms among people with no or subthreshold depression: a protocol for the Best, Efficient and Affordable Training in Resilience in Constant Evolution (BEATRICE) platform trial
Furukawa, T. A., Noma, H., Kojima, M., Tajika, A., Toyomoto, R., Sakata, M., Luo, Y., Kosuke Inoue, Horikoshi, M., Akechi, T., et al. (2026) · BMJ Open · doi:10.1136/bmjopen-2025-113603 · Cited by 1
“Among all participants judged to be NOT (regardless of their preceding interventions), we will use the Mixed Model for Repeated Measures (MMRM) 55 56 for the primary outcome of the change in the PHQ-8 from week 2 to week 6.”
Davanloos Intensive Psychodynamische Kurzzeittherapie
Johansson, R., Town, J. M., & Abbass, A. A. (2016) · Psychotherapeut · doi:10.1007/s00278-016-0108-1 · Cited by 1
Finite-sample performance of the robust variance estimator in the presence of missing data
Ishii, R., Maruo, K., Doi, M., & Gosho, M. (2022) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2022.2084107 · Cited by 1
“…situations, parameters of interest would be regarded as true; for example, the group effect parameter in a randomized clinical trial would be zero under the null hypothesis of no difference between groups (Gail, Wieand, and Piantadosi 1984; Mallinckrodt, Clark, and David 2001b; Barnes et al. 2008).”
BackgroundMethod
Statistical methods for clinical trials interrupted by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic: A review
Basu, J., Parsons, N., Friede, T., & Stallard, N. (2024) · Statistical Methods in Medical Research · doi:10.1177/09622802241288350 · Cited by 1
“Examples are the mixed model for repeated measures 41 in an RCT under MAR assumption for longitudinal continuous outcomes when the outcome vector is distributed as multivariate (MV) normal, generalised linear mixed models (GLMMs) 42,43 and generalised estimating equation (GEE) 44 models to deal…”
In-service teachers' perceptions of board games in teaching: Impact of the level of seriousness of the games and teachers’ characteristics
Jobert, N., & Sanchiz, M. (2025) · Teaching and Teacher Education · doi:10.1016/j.tate.2025.104951 · Cited by 12
Preoperative single-dose methylprednisolone versus placebo after major liver resection in adults: protocol for a randomised controlled trial
Bressan, A. K., Roberts, D. J., Bhatti, S. U., Dixon, E., Sutherland, F. R., Bathe, O. F., & Ball, C. G. (2015) · BMJ Open · doi:10.1136/bmjopen-2015-008948 · Cited by 1
Controlling alpha for mixed effects models for repeated measures
Ye, Z., & Bekele, B. N. (2018) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2018.1439052 · Cited by 1
“Mixed Effects Models for Repeated Measures (MMRM) (Mallinckrodt et al., 2001; Lindstrom and Bates, 1988), is often used to analyze such data, and the number of subjects in each analysis is not an accurate reflection of the information due to the dependence among the within-subject measurements.”
Method
The effect of an educational program for pregnant women to prevent allergic diseases in infants: study protocol for a randomized controlled trial
Nakamura, R., Ishiguro, N., Naru, E., Ishitsuka, Y., Nakade, M., & Nezu, Y. (2019) · Trials · doi:10.1186/s13063-019-3797-2 · Cited by 1
Estimation of group means using Bayesian generalized linear mixed models
Lalonde, A., & Qu, Y. (2020) · Pharmaceutical Statistics · doi:10.1002/pst.2006 · Cited by 1
“The popularity of MMRM and GLMMRM is derived from its ability to provide a consistent estimator for the parameter under the ignorability assumption when missing is at random (MAR).(10,11) While the primary analysis is to compare the response between treatments, it is also of interest to evaluate the response for each…”
Method
Comparison of Methods Dealing with Missing Data in a Longitudinal Rheumatologic Study
CAY, F., Fırat, M. Z., & Kaçar, C. (2021) · Akdeniz Medical Journal · doi:10.53394/akd.959358 · Cited by 1
“It has been demonstrated that LOCF can produce biased findings, resulting in overestimation or underestimating of parameter estimates (5), (21-24).”
Background
Bigotry in Last Observation Carried Forward (LOCF) Analysis
Sampoornam, W. (2022) · International Journal of Nursing Education and Research · doi:10.52711/2454-2660.2022.00005 · Cited by 1
Measuring Change
Zonderman, A. B., Dore, G. A., & Mode, N. A. (2022) · Springer eBooks · doi:10.1007/978-0-387-85960-6_60 · Cited by 1
Analysis and Sensitivity Analysis for Incomplete Longitudinal Data
Beunckens, C. (2007) · Document Server@UHasselt (UHasselt) · Cited by 1
Results for behavioural activation are overstated
Kripalani, M., & Suleman, M. (2013) · The British Journal of Psychiatry · doi:10.1192/bjp.202.6.466 · Cited by 1
Interpreting Antidepressant Clinical Trials
Sussman, N. (2007) · Annals of Clinical Psychiatry · doi:10.1080/10401230701653179 · Cited by 1
Response profiles for longitudinal clinical trial data with subject dropout under regulatory considerations
Mallinckrodt, C. H., Clark, S. W., Carroll, R. J., & Molenberghs, G. (2003) · Document Server@UHasselt (UHasselt) · Cited by 1
Self-citation
Chronic nicotinamide mononucleotide supplementation elevates blood nicotinamide adenine dinucleotide levels and alters muscle motility in healthy old menPreprint
Igarashi, M., Miura, M., Nakagawa-Nagahama, Y., Yaku, K., Kashiwabara, K., Sawada, M., Sekine, R., Fukamizu, Y., Sato, T., Sakurai, T., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-455083/v1 · Cited by 1
Identifying treatment effects using trimmed means when data are missing not at random
Ocampo, A., Schmidli, H., Quarg, P., Callegari, F., & Pagano, M. (2021) · Pharmaceutical Statistics · doi:10.1002/pst.2147
“The trimmed means approach can be extended to include covariates such as in an ANCOVA and can be applied in mixed models for repeated measures (MMRM) [10].”
Method
Author's response to “Comment on “Does ferric gluconate lower epoetin requirements in hemodialysis patients with high ferritin levels?””
Agarwal, R. (2008) · Nature Reviews Nephrology · doi:10.1038/ncpneph0966
Avaliação da troca do metilfenidato de liberação imediata para o metilfenidato de liberação prolongada no transtorno de déficit de atenção / hiperatividade
Maia, C. R. M. (2009) · Americanae (AECID Library)
Repeated Measures Analyses in Clinical Trials with Titration Visits
Dinh, P. V., & Yang, P. (2009) · Drug Information Journal · doi:10.1177/009286150904300508
placebo in major depressive disorder: use of a mixture model v. Assessing the 'true' effect of active antidepressant therapy
Thase, M. E., Larsen, K. G., & Kennedy, S. H. (2011)
Modélisation longitudinales de marqueur du VIH
Thiébaut, R. (2002) · HAL
dropout mechanisms using extended pattern mixture model
Gong, J. (2012)
Two-Period Designs for Evaluation of Disease-Modifying Treatments
McDermott, M. P. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9781139032445.012
Analysis and Sensitivity Analysis for Incomplete Longitudinal Data
Wetenschappen, F. (2007)
Missing Data in Clinical Trial: A Critical Look at the Proportionality of MNAR and MAR Assumptions for Multiple Imputation
Dipita, T. B. (2016)
Statistical Methodologies for Dealing with Incomplete Longitudinal Outcomes Due to Dropout Missing at Random
Satty, A., Mwambi, H. G., & Molenberghs, G. (2017) · ICSA book series in statistics · doi:10.1007/978-981-10-3307-0_10
Bias reduction using surrogate endpoints as auxiliary variables
Takagi, Y., & Kano, Y. (2018) · Annals of the Institute of Statistical Mathematics · doi:10.1007/s10463-018-0667-8
MMRM with Missing Data
Pong, A., Zhao, J. F., Lee, A. S., Phiri, P., & Sverdlov, L. (2018) · doi:10.1201/9781351110273-130001133
The Role of Procalcitonin Measurements in Predicting Clinical Outcomes in Critically Ill/Injured Patients
Rawahi, A. A. (2019) · doi:10.11575/prism/36748
Permutation Inference Methods for the MMRM (Mixed-Effects Model for Repeated Measures) in Incomplete Longitudinal Data Analysis
Ukyo, Y., & Noma, H. (2019) · Japanese Journal of Biometrics · doi:10.5691/jjb.40.15
P.012 During detoxification to patients diagnosed with cocaine use disorder, use of cannabis is associated with increased intensity of cocaine craving
Ramis, J. M. B., Alcaraz, S., Muñoz, L. R., Siñol, N., Duran‐Sindreu, S., Batlle, F., Trujols, J., & Cobos, J. P. D. L. (2020) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2020.09.018
School-Based Cognitive Behavioral Intervention Program For Addressing Anxiety In 10- To 11-Year-Olds Using Short Classroom Activities: A Quasi-Experimental StudyPreprint
Urao, Y., Yoshida, M., Sato, Y., & Shimizu, E. (2020) · Research Square · doi:10.21203/rs.3.rs-49225/v1
Utprøving av en tilpasset gruppebehandling for unge voksne
Try, E., Halmøy, A., Hufthammer, K. O., & Borge, L. (2021) · Tidsskrift for Norsk psykologforening · doi:10.52734/x5q9um84
Missing Data
Molenberghs, G., Beunckens, C., Jansen, I., Thijs, H., Verbeke, G. N., & Kenward, M. G. (2005) · Springer eBooks · doi:10.1007/978-3-540-26577-1_20
Missing Data
Molenberghs, G., & Lesaffre, E. M. E. H. (2005) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess7182
Bibliography
O’Kelly, M., & Ratitch, B. (2014) · doi:10.1002/9781118762516.biblio
Estimands for Continuous Longitudinal Outcomes in the Presence of Treatment Discontinuation—A Simulation Study in Hyperkalemia Treatments
Tsuchikawa, M., & Sakamaki, K. (2022) · Statistics in Biopharmaceutical Research · doi:10.1080/19466315.2022.2050289
MMRM with Missing Data
Pong, A., Lee, A., Zhao, J. F., Phiri, P., & Sverdlov, L. (2010) · Informa Healthcare eBooks · doi:10.3109/9781439822463.133
Peer Review #2 of "Affect-focused psychodynamic psychotherapy for depression and anxiety through the Internet: a randomized controlled trial (v0.1)"
(2013) · PeerJ · doi:10.7287/peerj.102v0.1/reviews/2
Conflict of interest declaration
(2007) · International Psychogeriatrics · doi:10.1017/s1041610207006990
Peer Review #1 of "Affect-focused psychodynamic psychotherapy for depression and anxiety through the Internet: a randomized controlled trial (v0.1)"
(2013) · PeerJ · doi:10.7287/peerj.102v0.1/reviews/1
Discussion
(2006) · Japanese Journal of Biometrics · doi:10.5691/jjb.27.s55
Peer Review #3 of "Affect-focused psychodynamic psychotherapy for depression and anxiety through the Internet: a randomized controlled trial (v0.1)"
(2013) · PeerJ · doi:10.7287/peerj.102v0.1/reviews/3
Estimands in clinical drug development: from design to regulatory assessment
Mitroiu, M. (2022) · Utrecht University Repository (Utrecht University) · doi:10.33540/723
Tui Na for painful peripheral neuropathy in people with human immunodeficiency virus: A randomized, double-blind, placebo-controlled trial protocol
Zhu, X., Song, G., Dune, L. S., Yang, C., Tian, C., & Wang, Y. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1113834
“The likelihoodbased MMRM can handle missingness in the responses when the responses are missing at random (50).”
Missing Data
Molenberghs, G., Beunckens, C., Jansen, I., Thijs, H., Verbeke, G. N., & Kenward, M. G. (2023) · Springer eBooks · doi:10.1007/978-1-4614-6625-3_20-1
Long-term effects of internet-based cognitive behavioral therapy on depression prevention among university students: a randomized controlled factorial trial. (Preprint)Preprint
Nakagami, Y., Uwatoko, T., Shimamoto, T., Sakata, M., Toyomoto, R., Yoshida, K., Luo, Y., Shiraishi, N., Tajika, A., Sahker, E., et al. (2024) · doi:10.2196/preprints.56691
Association between phase angle and clinical outcomes in patients with lumbar spinal stenosis from the preoperative to 12-month postoperative period: A prospective observational study
Wada, T., Tanishima, S., Kitsuda, Y., Osaki, M., Takeda, C., Noma, H., Nagashima, H., & Hagino, H. (2024) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2024.03.012
Effectiveness of an Instructional Design-Based Self-Management Program for Patients with Knee Osteoarthritis
Tanimura, C., Tokushima, Y., Yoshimura, J., Miyoshi, M., Matsumoto, H., Morita, T., Matsumoto, A., Ogura, Y., Nezu, M., Hagino, H., et al. (2025) · Yonago acta medica · doi:10.33160/yam.2025.02.003
Efficacy and mediators of online cognitive therapy for taboo obsessions in adults with obsessive-compulsive disorder: Randomized controlled trial
Lauri, K. O., Aspvall, K., Lybert, N., Samuelsson, C., Liliequist, B. E., Håkansson, E., Serlachius, E., Rück, C., Mataix-Cols, D., & Andersson, E. (2025) · Behaviour Research and Therapy · doi:10.1016/j.brat.2025.104708
Fast autoregressive model for multivariate dependent outcomes with application to lipidomics analysis for Alzheimer’s disease and APOE- ε 4
Lee, H., Ye, Z., Chen, C., Kochunov, P. V., Hong, L. E., & Chen, S. (2025) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2025.108280
Additional file 1 of The evaluation of a physical health promotion intervention for people with severe mental illness receiving community based accommodational support: a mixed-method pilot study
Kirschner, V. S., Lamp, N., Dinc, Ü., Becker, T., Kilian, R., & Mueller-Stierlin, A. S. (2022) · Figshare · doi:10.6084/m9.figshare.17870326
Additional file 1 of ACE inhibitors and angiotensin receptor blockers differentially alter the response to angiotensin II treatment in vasodilatory shock
Leisman, D. E., Handisides, D. R., Busse, L. W., Chappell, M. C., Chawla, L. S., Filbin, M. R., Goldberg, M. B., Ham, K. R., Khanna, A. K., Ostermann, M., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26708750
Treatment for Migraine and Mood (TEAM-M) study: Protocol for a three-arm multi-site randomized controlled feasibility trial comparing an abbreviated version of mindfulness-based cognitive therapy delivered via telephone or videoconferencing to enhanced usual care (Preprint)Preprint
Siwik, C. J., Tankha, H., Hill, J. D., Visvanathan, P. D., Gaskins, D., DeSciscio, M., McCarty, N. P., O’Brien, H., Salvaterra, M., Wang, C., et al. (2026) · doi:10.2196/preprints.93627
Effects of a Fermented Sake Lees Product and Kwanso Concentrated Extract on Morning Drowsiness in Physically and Mentally Healthy Japanese Adults
Takizawa, J., Suzuki, N., & Takara, T. (2026) · Nippon Eiyo Shokuryo Gakkaishi · doi:10.4327/jsnfs.79.65
Effects of smartphone cognitive behavioural therapy on social functioning in non-depressive and subthreshold depressive adults: a secondary analysis of the RESiLIENT trial
Tajika, A., Toyomoto, R., Sakata, M., Luo, Y., Akechi, T., Horikoshi, M., Inoue, K., Noma, H., Cuijpers, P. J., & Furukawa, T. A. (2026) · BMJ Mental Health · doi:10.1136/bmjment-2025-302303
“The MMRM, based on the direct likelihood principle, accounts for bias arising from outcome missingness under a missing- at-random mechanism and provides statistically valid inferences.”
Acute Cortical Excitability Change is Associated with Long-Term Working Memory Improvement by HD-tDCS Treatment in Schizophrenia: a TMS-EEG Study
Chen, K., Li, X., Tang, R., Xu, Y., Zhuang, W., Chen, Z., Fu, J., Zhang, C., Li, L., Shao, Y., et al. (2025) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf241
App-based skills training to reduce problem drinking among adult internet help-seekers: a double-blinded randomized controlled trial
Chen, Y., Berman, A. H., Andersson, C., Blankers, M., & Molander, O. (2026) · Addiction Science & Clinical Practice · doi:10.1186/s13722-026-00663-5
“…imputation, mixed-effects repeated measures approaches produce valid inferences under the missing at random assumption and have been shown to yield less biased treatment effect estimates and standard errors compared with last observation carried forward or single-imputa-tion methods [72, 73].”
A multicenter, randomized, double-blinded, placebo-controlled phase III trial to evaluate efficacy and safety of picankibart in moderate-to-severe plaque psoriasis
Gao, Y., Qin, L., Li, Y., Cui, Y., Zhang, S., Liu, L., Wang, L., Ci, C., Lu, J., Chen, R., et al. (2026) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2026.04.001
Evaluating an Abbreviated Version of Mindfulness-Based Cognitive Therapy Delivered via Telephone or Videoconferencing Compared to Enhanced Usual Care—Treatment for Migraine and Mood (TEAM-M) Study: Protocol for a Three-Arm Multisite Randomized Controlled Feasibility Trial
Siwik, C. J., Tankha, H., Hill, J. D., Visvanathan, P. D., Gaskins, D., DeSciscio, M., McCarty, N. P., O’Brien, H., Salvaterra, M., Wang, C., et al. (2026) · JMIR Research Protocols · doi:10.2196/93627
“Mixed models allow for unbiased parameter estimations, even when data are not missing at random [47].”
Evaluating load shifting controls in 23 heat pump water heaters in multi-family residencesPreprint
Zou, A., Close, B., Ellis, M. J., Feng, J., Hacking, D., Meyers, F., Outcault, S. M., Perea, C., Raftery, P., Rosa, L. D., et al. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7305258
Covariate-adaptive randomization with dropouts
Sung, M.-H., Xiao, Q., & Shen, Y. (2026) · Statistical Methods in Medical Research · doi:10.1177/09622802261475671
Study Protocol for the Daasanach Human Biology Project: A Longitudinal Study of the Impact of Drinking Water Salinity and Heat Stress on Water Insecurity, Hydration, Energetics, Hypertension, and Kidney Function in Northern Kenya
Rojas, A., Ndiema, E., Nzunza, R., Hunter, M. D., Sands, J. M., Farquhar, W., Kenney, W. L., Roba, K. T., McGrosky, A., Douglass, M., et al. (2026) · American Journal of Human Biology · doi:10.1002/ajhb.70343
“Our analytic strategy of multilevel models handles attrition well (Mallinckrodt et al. 2001).”
Translabial 3D ultrasound for diagnosing levator ani defects in women with pelvic organ prolapse
Notten, K. J. B. (2015) · Research Publications (Maastricht University) · doi:10.26481/dis.20150521kn
Tilläggsbehandling som återfallsprevention efter internetadministrerad KBT vid tvångssyndrom : - en randomiserad kontrollerad studie
Söderholm, P., & Brander, G. (2013) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Strategies for dealing with missing data in clinical trials: from design to analysis.
(2013) · PubMed Central · Cited by 288

Authors: Mallinckrodt, C. H., Clark, W. S., & David, S. R.
Affiliations: Eli Lilly (United States) (US)
ORCID: Mallinckrodt, Craig H.
Venue: Journal of Biopharmaceutical Statistics
Publisher: Informa UK Limited
Published: 2001-01-01
Volume: 11
Issue: 1-2
Pages: 9-21
ISSN: 1054-3406 (ISSN-L)
1520-5711
DOI: 10.1081/bip-100104194
OpenAlex: W2073155558
Cited by: 398
References: 14
Citations by year: 2026: 12 · 2025: 13 · 2024: 21 · 2023: 12 · 2022: 27 · 2021: 19 · 2020: 20 · 2019: 13 · 2018: 14 · 2017: 14 · 2016: 18 · 2015: 21 · 2014: 16 · 2013: 23 · 2012: 19
FWCI: 11.96
Type: journal article
Language: en
Open access: closed
Locations: Journal of Biopharmaceutical Statistics (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords: mixed models, last observation carried forward, missing data, non-ignorable missingness, treatment effect estimation, longitudinal data, randomized controlled trials, standard error estimation
MeSH terms: Analysis of Variance, Humans, Longitudinal Studies, Patient Dropouts, Models, Statistical, Bias, Confidence Intervals, Randomized Controlled Trials as Topic

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

ACCOUNTING FOR DROPOUT BIAS USING MIXED-EFFECTS MODELS

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks