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 201–300 of 398

Pragmatic randomised controlled trials in parenting research: the issue of intention to treat
Whittaker, K. A., Sutton, C., & Burton, C. (2006) · Journal of Epidemiology & Community Health · doi:10.1136/jech.2005.044214 · Cited by 20
Subjective wellbeing under quetiapine treatment: Effect of diagnosis, mood state, and anxiety
Lambert, M., Naber, D., Karow, A., Huber, C. G., Köhler, J., Heymann, J., & SCHIMMELMANN, B. G. (2009) · Schizophrenia Research · doi:10.1016/j.schres.2009.03.004 · Cited by 20
Conceptual Considerations regarding Endpoints, Hypotheses, and Analyses for Incomplete Longitudinal Clinical Trial Data
Mallinckrodt, C. H., & Kenward, M. G. (2009) · Drug Information Journal · doi:10.1177/009286150904300410 · Cited by 19
Self-citation
Improved health of hospitality workers after a Swiss cantonal smoking ban
Durham, A., Bergier, S., Morisod, X., Locatelli, I., Jp, Z., & Huynh, C. (2011) · Swiss Medical Weekly · doi:10.4414/smw.2011.13317 · Cited by 19
Alemtuzumab improves contrast sensitivity in patients with relapsing–remitting multiple sclerosis
Graves, J. S., Galetta, S. L., Palmer, J. P., Margolin, D. H., Rizzo, M., Bilbruck, J., & Balcer, L. J. (2013) · Multiple Sclerosis Journal · doi:10.1177/1352458513475722 · Cited by 19
Study protocol: münster tinnitus randomized controlled clinical trial-2013 based on tailor-made notched music training (TMNMT)
Pantev, C., Rudack, C., Stein, A., Wunderlich, R., Engell, A., Lau, P., Wollbrink, A., & Shaykevich, A. (2014) · BMC Neurology · doi:10.1186/1471-2377-14-40 · Cited by 19
“In anticipation of dropouts and missing data, a likelihoodbased mixed-effects model for repeated measures analysis [33] was chosen as the primary analysis.”
Method
Bivariate Longitudinal Model For The Analysis Of The Evolution Of Hiv Rna And Cd4 Cell Count In Hiv Infection Taking Into Account Left Censoring Of Hiv Rna Measures
Thiébaut, R., Jacqmin‐Gadda, H., Leport, C., Katlama, C., Costagliola, D. G., Moing, V. L., Morlat, P., Chêne, G., & the Aproco Study Group (2003) · Journal of Biopharmaceutical Statistics · doi:10.1081/bip-120019271 · Cited by 19
“In fact, inferences of linear mixed models are valid if the missingness mechanism is ignorable in the likelihood (Mallinckrodt et al., 2001), which implies that data are missing at random Bivariate Longitudinal Model 279 MARCEL DEKKER, INC.”
Background
Evaluating the evidence base for university counseling services and their effectiveness using core measures: A systematic review and meta-analysis.
Collins, C., Broglia, E., & Barkham, M. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.12.022 · Cited by 16
Taylor Spatial Frame or Reamed Intramedullary Nailing for Closed Fractures of the Tibial Shaft: A Randomized Controlled Trial
Frihagen, F., Madsen, J. E., Sundfeldt, M., Flugsrud, G. B., Andreassen, J. S., Andersen, M. R., & Andreassen, G. S. (2020) · Journal of Orthopaedic Trauma · doi:10.1097/bot.0000000000001802 · Cited by 19
The impact of dichotomization in longitudinal data analysis: a simulation study
Yoo, B. (2010) · Pharmaceutical statistics · doi:10.1002/pst.396 · Cited by 16
Patient-centred innovation for multimorbidity care: a mixed-methods, randomised trial and qualitative study of the patients’ experience
Stewart, M., Fortin, M., Brown, J. B., Ryan, B. L., Pariser, P., Charles, J., Pham, T.-N. T., Boeckxstaens, P., Reichert, S. M., Zou, G., et al. (2020) · British Journal of General Practice · doi:10.3399/bjgp21x714293 · Cited by 17
Development of hip displacement in cerebral palsy: a longitudinal register study of 1,045 children
Wagner, P., & Hägglund, G. (2021) · Acta Orthopaedica · doi:10.2340/17453674.2021.851 · Cited by 17
“The MM allowed us to account, at least in part, for systematic inclusion and dropouts (11) and to quantify individual developmental heterogeneity.”
Genetic propensity, socioeconomic status, and trajectories of depression over a course of 14 years in older adults
Kosciuszko, M., Steptoe, A., & Ajnakina, O. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02367-9 · Cited by 23
“LMMs with maximum likelihood estimation models maximise the use of longitudinal data, adjust for the correlation between repeated measures, weight estimates for missing data between waves, and increase statistical power and precision [40].”
Method
On the practical application of mixed effects models for repeated measures to clinical trial data
Andersen, S. W., & Millen, B. A. (2012) · Pharmaceutical Statistics · doi:10.1002/pst.1548 · Cited by 17
Sources and handling of losses to follow-up in parallel-group randomized clinical trials in dogs and cats: 63 trials (2000–2005)
Brown, D. C. (2007) · American Journal of Veterinary Research · doi:10.2460/ajvr.68.7.694 · Cited by 18
Individual and County-Level Factors Associated with Use of Multiple Prescribers and Multiple Pharmacies to Obtain Opioid Prescriptions in California
Han, H., Kass, P. H., Wilsey, B. L., & Li, C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046246 · Cited by 17
“The latter was calculated as the interval between an individual’s first and last opioid prescriptions in 2006 plus an estimate of the duration of his/her last prescription utilizing the ‘‘last observation carry forward’’ method [30,31].”
Method
Effectiveness of a cognitive behavioural therapy-based anxiety prevention programme for children: a preliminary quasi-experimental study in Japan
Urao, Y., Yoshinaga, N., Asano, K., Ishikawa, R., Tano, A., Sato, Y., & Shimizu, E. (2016) · Child and Adolescent Psychiatry and Mental Health · doi:10.1186/s13034-016-0091-x · Cited by 19
“Under the ignorable missing data framework, MMRM analysis appears to be a robust approach in estimating the true treatment difference and in controlling Type I error rates [45, 46].”
Method
Estimation of treatment effects in short‐term depression studies. An evaluation based on the ICH E9 ( R1 ) estimands framework
Mitroiu, M., Teerenstra, S., Rengerink, K. O., Pétavy, F., & Roes, K. C. B. (2022) · Pharmaceutical Statistics · doi:10.1002/pst.2214 · Cited by 17
Randomization in clinical trials: can we eliminate bias?
Sverdlov, O., & Rosenberger, W. F. (2012) · Clinical Investigation · doi:10.4155/cli.12.130 · Cited by 18
How antipsychotics impact the different dimensions of Schizophrenia: A test of competing hypotheses
Marques, T. R., Levine, S. Z., Reichenberg, A., Kahn, R. S., Derks, E. M., Fleischhacker, W., Rabinowitz, J., & Kapur, S. (2014) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2014.04.001 · Cited by 17
“LOCF is, nevertheless, considered by some to be superior as it takes the last observation with exacerbation prior to dropout, is standard clinical trial practice and is more conservative to imputation and use of observed cases (Mallinckrodt et al., 2001a, 2001b; Rabinowitz and Davidov, 2008).”
Handling Baselines in Repeated Measures Analyses with Missing Data at Random
Dinh, P. V., & Yang, P. (2011) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2011.550113 · Cited by 17
Effectiveness of Open-Ended Psychotherapy Under Clinically Representative Conditions
Nordmo, M., Sønderland, N. M., Havik, O. E., Eilertsen, D., Monsen, J. T., & Solbakken, O. A. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00384 · Cited by 19
“, last observation carried forward method) when handling missing data and accounting for potential dropout bias (32, 33).”
Method
Grief-Specific Cognitive Behavioral Therapy vs Present-Centered Therapy: A Randomized Clinical Trial.
Rosner, R., Rau, J., Kersting, A., Rief, W., Steil, R., Rummel, A.-M., Vogel, A., & Comtesse, H. (2024) · JAMA psychiatry · doi:10.1001/jamapsychiatry.2024.3409 · Cited by 17
Drug-dependent inpatients reporting continuous absence of spontaneous drug craving for the main substance throughout detoxification treatment
Cobos, J. P. D. L., Siñol, N., Trujols, J., Bañuls, E. F., BATLLE, F., & Tejero, A. (2010) · Drug and Alcohol Review · doi:10.1111/j.1465-3362.2010.00241.x · Cited by 16
Health-related quality of life in patients with locally recurrent or metastatic breast cancer treated with etirinotecan pegol versus treatment of physician's choice: Results from the randomised phase III BEACON trial
Twelves, C. J., Cortés, J., O’Shaughnessy, J., Awada, A. H., Perez, E. A., Im, S., Gómez-Pardo, P., Schwartzberg, L. S., Dieras, V. C., Yardley, D. A., et al. (2017) · European Journal of Cancer · doi:10.1016/j.ejca.2017.02.011 · Cited by 16
“Change from baseline over time was analysed by repeated measures linear mixed effects (Mixed effect Model Repeat Measurement or MMRM) [24,25] for domains/symptoms with multiple questions and generalised linear mixed models (GLMM) for domains/symptoms with a single question [26].”
MethodInfluential
LiMA: a study protocol for a randomised, double-blind, placebo controlled trial of lisdexamfetamine for the treatment of methamphetamine dependence
Ezard, N., Dunlop, A. J., Hall, M., Ali, R. L., McKetin, R., Bruno, R., Phung, N., Carr, A. D., White, J. M., Clifford, B., et al. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-020723 · Cited by 16
“No imputation of missing data will be performed under MMRM approach, the MMRM analysis makes use of all available data and is reliable for effect and SE estimates under missing at random (MAR) assumption.(36) Sensitivity analysis including baseline observation carried forward imputation will be performed to investigat…”
Method
Interpretable inference on the mixed effect model with the Box-Cox transformation
Maruo, K., Yamaguchi, Y., Noma, H., & Gosho, M. (2017) · Statistics in Medicine · doi:10.1002/sim.7279 · Cited by 16
“We applied the proposed method based on the model-based and the robust variance estimators with the empirical adjustments, the method proposed by Maruo et al. [6] for the CCA and the LOCF data, and the MMRM methods on the original and log-transformed scale, where the inferences for differences of the treatment effects…”
MethodInfluential
A Likelihood-Based Approach for the Analysis of Longitudinal Clinical Trials with Return-to-Baseline Imputation
Zhang, Y., Golm, G. T., & Liu, G. F. (2020) · Statistics in Biosciences · doi:10.1007/s12561-020-09269-0 · Cited by 13
Sustained reduction in health care costs after adjunctive treatment of graded intensive short-term dynamic psychotherapy in patients with psychotic disorders
Abbass, A. A., Bernier, D. C., Kisely, S. R., Town, J. M., & Johansson, R. (2015) · Psychiatry Research · doi:10.1016/j.psychres.2015.05.056 · Cited by 14
“This form of estimation provides unbiased estimates under the less restrictive assumption of data missing at random (MAR; Mallinckrodt et al., 2001), which allows the probability of data being missing to be dependent of the outcome variables (e.”
Difelikefalin for Hemodialysis Patients with Pruritus in Japan
Narita, I., Tsubakihara, Y., Takahashi, N., Ebata, T., Uchiyama, T., Marumo, M., Okamura, S., Gejyo, F., & MR13A9-5 Trial Investigators (2023) · NEJM Evidence · doi:10.1056/evidoa2300094 · Cited by 14
Condensed Internet-delivered prolonged exposure provided soon after trauma: a randomised trial
Bragesjö, M., Arnberg, F. K., Lauri, K. O., Aspvall, K., Särnholm, J., & Andersson, E. (2021) · Psychological Medicine · doi:10.1017/s0033291721003706 · Cited by 14
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. M., Kilian, R., & Mueller‐Stierlin, A. S. (2022) · BMC Psychiatry · doi:10.1186/s12888-021-03640-1 · Cited by 16
“Missing values were taken into account by weighting of the parameter estimation [54, 55].”
Method
Prediction of Disease Progression, Treatment Response and Dropout in Chronic Obstructive Pulmonary Disease (COPD)
Musuamba, F. T., Teutonico, D., Maas, H. J., Facius, A., Yang, S., Danhof, M., & Pasqua, O. E. D. (2014) · Pharmaceutical Research · doi:10.1007/s11095-014-1490-4 · Cited by 14
Feasibility of Training Frontline Therapists in Prolonged Exposure
Ghafoori, B., Hansen, M. C., Garibay, E., & Korosteleva, O. (2017) · The Journal of Nervous and Mental Disease · doi:10.1097/nmd.0000000000000659 · Cited by 15
A simulation study comparing slope model with mixed‐model repeated measure to assess cognitive data in clinical trials of Alzheimer's disease
Chen, Y., Ni, X., Fleisher, A., Zhou, W., Aisen, P. S. S., & Mohs, R. C. (2018) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1016/j.trci.2017.12.002 · Cited by 14
“demonstrated that mixed-effects models, particularly the MMRMwith unstructured mean and within-subject error correlation, provide more accurate estimates of treatment effect and its standard error than last observation carried forward analysis of covariance when data are missing at random [2].”
Method
Effects of Symptom Reduction and Psychotropic Medication on Cognitive Impairment in Depression
Frasch, K., Bullacher, C., Jäger, M., Kilian, R., Rink, M., Wittek, R., Becker, T., & Neumann, N.-U. (2009) · Psychopathology · doi:10.1159/000187635 · Cited by 14
Treating depression and its comorbidity : From individualized Internet-delivered cognitive behavior therapy to affect-focused psychodynamic psychotherapy
Johansson, R. (2013) · Linköping studies in behavioural science · doi:10.3384/diss.diva-100385 · Cited by 13
Optimizing smartphone psychotherapy for depressive symptoms in patients with cancer: Multiphase optimization strategy using a decentralized multicenter randomized clinical trial (J‐SUPPORT 2001 Study)
Akechi, T., Furukawa, T. A., Noma, H., Iwata, H., Toyama, T., Higaki, K., Matsuoka, H., Zenda, S., Iwatani, T., Akahane, K., et al. (2024) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13657 · Cited by 13
“We used mixed-effects repeated-measures analysis 38 to estimate the mean difference in PHQ-9 change scores for each component (primary analysis).”
Method
Improving sleep quality in climacteric women with insomnia: A randomized, head-to-head trial between Jia-Wei-Shiau-Yau San (JWSYS) and Suan-Zao-Ren Tang (SZRT)
Wu, H.-C., Chen, Y., Lai, J., Hwang, J.-S., & Wang, J. (2011) · European Journal of Integrative Medicine · doi:10.1016/j.eujim.2011.08.009 · Cited by 13
Hip development after surgery to prevent hip dislocation in cerebral palsy: a longitudinal register study of 252 children
Wagner, P., & Hägglund, G. (2021) · Acta Orthopaedica · doi:10.1080/17453674.2021.1989563 · Cited by 13
Delayed- and early-onset hypotheses of antipsychotic drug action in the negative symptoms of schizophrenia
Levine, S. Z., & Leucht, S. (2012) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2012.03.001 · Cited by 13
Remission With Venlafaxine Extended Release or Selective Serotonin Reuptake Inhibitors in Depressed Patients
Thase, M. E., Ninan, P. T., Musgnung, J. J., & Trivedi, M. H. (2011) · The Primary Care Companion For CNS Disorders · doi:10.4088/pcc.10m00979blu · Cited by 15
A latent variable approach in simultaneous modeling of longitudinal and dropout data in schizophrenia trials
Goyal, N., & Goméni, R. (2013) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2013.03.004 · Cited by 13
Mixed Models for Repeated Measures using Categorical time Effects (MMRM)
Thomas, S. (2014) · doi:10.1002/9781118762516.ch5 · Cited by 13
Best practices and pragmatic approaches for patient-reported outcomes and quality of life measures in cancer clinical trials
Bandos, H., Torres‐Saavedra, P. A., Culakova, E., Gunn, H., Lee, M. K., Duan, F., Cecchini, R. S., Unger, J. M., Dueck, A. C., & Steingrimsson, J. A. (2024) · JNCI Monographs · doi:10.1093/jncimonographs/lgae047 · Cited by 11
Add-on treatment with N-acetylcysteine for bipolar depression: a 24-week randomized double-blind parallel group placebo-controlled multicentre trial (NACOS-study protocol)
Ellegaard, P. K., Licht, R. W., Poulsen, H. E., Nielsen, R. E., Berk, M., Dean, O. M., Mohebbi, M., & Nielsen, C. T. (2018) · International Journal of Bipolar Disorders · doi:10.1186/s40345-018-0117-9 · Cited by 12
“2001) approach will be taken, and the likelihood-based linear mixed effects repeated measures (LMERM) analyses (Mallinckrodt et al. 2001; Laird and Ware 1982) is the primary analysis.”
Method
Fast tipping point sensitivity analyses in clinical trials with missing continuous outcomes under multiple imputation
Gorst‐Rasmussen, A., & Tarp-Johansen, M. J. (2022) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2022.2058525 · Cited by 12
Switching from methylphenidate immediate release to MPH-SODAS™ in attention-deficit/hyperactivity disorder
Maia, C. R. M., Matte, B. C., Ludwig, H. T., & Rohde, L. A. (2007) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-007-0647-7 · Cited by 12
“Analyses of efficacy and side events were performed using a Mixed-Effects Model (MEM) approach which provides a flexible framework for the analysis of repeated measures while accounting for missing data (lost of follow-up) [17, 25].”
Method
Effects of a co-created occupational health intervention on stress and psychosocial working conditions within the construction industry: A controlled trial
Cedstrand, E., Augustsson, H., Alderling, M., Sánchez-Martínez, N., Bodin, T., Nyberg, A., & Johansson, G. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.973890 · Cited by 11
Missing Data in Noninferiority Trials
Wiens, B. L., & Rosenkranz, G. K. (2013) · Statistics in Biopharmaceutical Research · doi:10.1080/19466315.2013.847383 · Cited by 11
“Introductory material on noninferiority trials can be found in Rothmann, Wiens, and Chan (2011). Missing data has been discussed thoroughly in the literature for superiority studies and it is recognized that handling missing data inappropriately can result in biased analyses.”
BackgroundMethod
Cost-effectiveness of an internet-based booster program for patients with obsessive–compulsive disorder: Results from a randomized controlled trial
Andersson, E., Ljótsson, B., Hedman‐Lagerlöf, E., Mattson, S., Enander, J., Andersson, G., Kaldo, V., Lindefors, N., & Rück, C. (2014) · Journal of Obsessive-Compulsive and Related Disorders · doi:10.1016/j.jocrd.2014.10.002 · Cited by 11
IMPROVE, a community-based exercise intervention versus support group to improve functional and health outcomes among older African American and non-Hispanic White breast cancer survivors from diverse socioeconomic backgrounds: Rationale, design and methods
Owusu, C., Nock, N. L., Hergenroeder, P., Austin, K., Bennet, E., Cerne, S., Moore, H. C. F., Petkac, J., SCHLUCHTER, M. D., Schmitz, K. H., et al. (2020) · Contemporary Clinical Trials · doi:10.1016/j.cct.2020.106001 · Cited by 11
Is there a SSRI dose response in treating major depression? The case for re-analysis of current data and for enhancing future study design
Baker, C. B., & Woods, S. W. (2003) · Depression and Anxiety · doi:10.1002/da.10076 · Cited by 11
Postpartum Weight Retention: A Retrospective Data Analysis Measuring Weight Loss and Program Engagement with a Mobile Health Program
Toro‐Ramos, T., Heaner, M. K., Yang, Q., DeLuca, L., Behr, H., Reynolds, K., Kim, Y., & Michaelides, A. P. (2021) · Journal of Women s Health · doi:10.1089/jwh.2020.8584 · Cited by 11
“34 All users in the program were analyzed despite any missingness related to completion status; weight outcomes were predicted from the linear mixed models conducted.”
The role of threat anticipation in the development of psychopathology in adolescence: findings from the SIGMA Study
Paetzold, I., Gugel, J., Schick, A., Kirtley, O. J., Achterhof, R., Hagemann, N., Hermans, K. S. F. M., Hiekkaranta, A. P., Lecei, A., Myin‐Germeys, I., et al. (2022) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-022-02048-w · Cited by 10
“We used random intercept and slope models and applied restricted maximum likelihood (H1 and H2) or maximum likelihood estimation (H3), allowing for the use of all available data under the relatively unrestrictive assumption that data are missing at random and all variables associated with missing values are included i…”
Method
Randomized Controlled Trial of a Virtually Delivered Exercise and Stress Management Program to Improve Physical Performance of Hematopoietic Cell Transplant Survivors
Ma, D. D. F., Liu, Z., Au, K., Tran, M. J., Artuz, C. M., Greenwood, M. J., Bilmon, I., & Kliman, D. S. (2024) · Journal of Clinical Oncology · doi:10.1200/jco.24.00333 · Cited by 11
“31 The outcome variables include the postintervention outcome measures (1.5, 3, 6, and 12 months).”
Influential
Post-exercise, passive heat acclimation with sauna or hot-water immersion provide comparable adaptations to performance in the heat in a military context
Ashworth, E. T., Cotter, J. D., & Kilding, A. E. (2022) · Ergonomics · doi:10.1080/00140139.2022.2058096 · Cited by 10
Association between polygenic propensity for psychiatric disorders and nutrient intake
Hunjan, A. K., Hübel, C., Lin, Y., Eley, T. C., & Breen, G. D. (2021) · Communications Biology · doi:10.1038/s42003-021-02469-4 · Cited by 10
Missing Data Imputation in Two Phase III Trials Treating HIV1 Infection
Huson, L., Chung, J., & Salgo, M. (2006) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543400601001535 · Cited by 10
“The design of our simulation study followed the general strategy employed by authors of other simulation studies of imputation methods (e.g., Cozzi Lepri et al., 1998; Mallinckrodt et al., 2001; Tang et al., 2005), using a combination of different longitudinal data patterns, percentages of missing data, sample sizes,…”
MethodInfluential
Efficient two-step multivariate random effects meta-analysis of individual participant data for longitudinal clinical trials using mixed effects models
Noma, H., Maruo, K., Gosho, M., Levine, S. Z., Goldberg, Y., Leucht, S., & Furukawa, T. A. (2019) · BMC Medical Research Methodology · doi:10.1186/s12874-019-0676-1 · Cited by 10
“As mentioned regarding the second issue in the previous section, when the time variables are often treated as factor variables (e.g., for the typical MMRM analyses [19]), the one-step approach has practical and computational difficulties.”
MethodInfluential
Weight Loss and Attrition in Overweight and Obese Young Women During a 36- Week Internet-Based Lifestyle Intervention
Lim, S. S. (2014) · Journal of Obesity & Weight loss Therapy · doi:10.4172/2165-7904.1000235 · Cited by 9
“This method has been shown to produce estimates closer to true values compared to the other conventional methods of handling missing data such as the lastobservation-carried-forward method [44].”
Method
Associations between responses to voices, distress and appraisals during daily life: an ecological validation of the cognitive behavioural model
Fielding-Smith, S. F., Greenwood, K., Wichers, M., PETERS, E. R., & Hayward, M. (2020) · Psychological Medicine · doi:10.1017/s0033291720002238 · Cited by 9
Cost-Effectiveness Inferences from Bootstrap Quadrant Confidence Levels: Three Degrees of Dominance
Obenchain, R. L., Robinson, R. L., & Swindle, R. W. (2005) · Journal of Biopharmaceutical Statistics · doi:10.1081/bip-200056525 · Cited by 9
“The mixed models repeated measures (MMRM) method of ( 2001 ), ( 2001 ) is particularly attractive because it can be used as a primary analysis; the MMRM approach does not require imputation of missing values.”
Grip Strength Trajectories and Cognition in English and Chilean Older Adults: A Cross-Cohort Study
Bárbara Angel, B., Ajnakina, O., Cecilia Albala, B., Lydia Lera, M., Márquez, C., Leipold, L., Bilovich, A., Dobson, R., & Bendayan, R. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12081230 · Cited by 9
“To examine the grip strength trajectories over time, linear mixed models (LMMs) with random coefficients [78] were estimated.”
Method
Assessing the efficacy and safety of STOP (successful treatment for paranoia)—an app-based cognitive bias modification therapy for paranoia: a randomised clinical trial protocol
Yiend, J., Taher, R., Fialho, C., Hampshire, C., Hsu, C.-W., Kabir, T., Keppens, J., McGuire, P. K., Mouchlianitis, E. D., PETERS, E. R., et al. (2024) · Trials · doi:10.1186/s13063-024-08570-3 · Cited by 7
Efficacy and Safety Study of Wearable Cyborg HAL (Hybrid Assistive Limb) in Hemiplegic Patients With Acute Stroke (EARLY GAIT Study): Protocols for a Randomized Controlled Trial
Watanabe, H., Marushima, A., Kadone, H., Shimizu, Y., Kubota, S., Hino, T., Sato, M., Ito, Y., Hayakawa, M., Tsurushima, H., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.666562 · Cited by 8
Sensitivity of individual items of the Positive and Negative Syndrome Scale (PANSS) and items subgroups to differentiate between placebo and drug treatment in schizophrenia
Kozielska, M., Reddy, V. P., Johnson, M. G., Ridder, F. D., Vermeulen, A., Liu, J., Groothuis, G. M. M., Danhof, M., & Proost, J. H. (2013) · Schizophrenia Research · doi:10.1016/j.schres.2013.01.022 · Cited by 8
“[13,14] These models take into account all observations taken during the time course of the trial.”
Missing Data
Molenberghs, G., & Lesaffre, E. M. E. H. (2006) · Wiley Encyclopedia of Clinical Trials · doi:10.1002/9780471462422.eoct044 · Cited by 8
Initiation of symptomatic medication in Alzheimer's disease clinical trials: Hypothetical versus treatment policy approach
Donohue, M., Model, F., Delmar, P., Volye, N., Liu‐Seifert, H., Rafii, M. S., Aisen, P. S. S., & Initiative, A. D. N. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.12058 · Cited by 7
Multiple imputation for longitudinal data using Bayesian lasso imputation model
Yamaguchi, Y., Yoshida, S., Misumi, T., & Maruo, K. (2022) · Statistics in Medicine · doi:10.1002/sim.9315 · Cited by 7
Results from a randomized controlled trial investigating effectiveness of a community-based intervention on empowerment of people with severe mental illness
Mueller‐Stierlin, A. S., Becker, T. M., Greve, N., Hänsel, A., Herder, K., Kohlmann, A., Lehle, J., Majewsky, U., Meixner, F., Prestin, E., et al. (2025) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-025-02879-3 · Cited by 6
“LMER using full information maximum likelihood estimators (FIML) allows the inclusion of the total sample by taking into account missing observations under the missing at random (MAR) assumption [40].”
Optimization of smartphone psychotherapy for depression and anxiety among patients with cancer using the multiphase optimization strategy (MOST) framework and decentralized clinical trial system (SMartphone Intervention to LEssen depression/Anxiety and GAIN resilience: SMILE AGAIN project): a protocol for a randomized controlled trial
Uchida, M., Furukawa, T. A., Yamaguchi, T., Imai, F., Momino, K., Katsuki, F., Sakurai, N., Miyaji, T., Horikoshi, M., Iwata, H., et al. (2023) · Trials · doi:10.1186/s13063-023-07307-y · Cited by 6
Changes in ocular blood flow in patients with neovascular age-related macular degeneration after intravitreal injection of ranibizumab biosimilar and brolucizumab
TAKIZAWA, H., Yasuda, M., Hoshi, K., Okabe, T., Kunikata, H., & Nakazawa, T. (2024) · International Ophthalmology · doi:10.1007/s10792-024-03107-8 · Cited by 7
“A mixed-effect model for repeated measures (MMRM) [21] was used for statistical analysis: MBR was the response variable and age, gender, the drug group (ranibizumab biosimilar or brolucizumab), time, and the drug group by time interaction were treated as fixed effects.”
bcmixed: A Package for Median Inference on Longitudinal Data with the Box–Cox Transformation
Maruo, K., Ishii, R., Yamaguchi, Y., & Gosho, M. (2021) · The R Journal · doi:10.32614/rj-2021-083 · Cited by 6
“Therefore, Maruo et al. (2017) applied the following empirical small sample adjustment for the inferences of the model median differences by referring to the study in Schluchter and Elashoff (1990).”
MethodInfluential
The long-term effects of a polygenetic predisposition to general cognition on healthy cognitive ageing: evidence from the English Longitudinal Study of Ageing
Ajnakina, O., Murray, R. M., Steptoe, A., & Cadar, D. (2022) · Psychological Medicine · doi:10.1017/s0033291721004827 · Cited by 6
Points to consider for analyzing efficacy outcomes in long‐term extension clinical trials
Ratitch, B., Lipkovich, I. A., Erickson, J., Zhang, L., & Mallinckrodt, C. H. (2018) · Pharmaceutical Statistics · doi:10.1002/pst.1888 · Cited by 6
Self-citation
A note on the bias of standard errors when orthogonality of mean and variance parameters is not satisfied in the mixed model for repeated measures analysis
Maruo, K., Ishii, R., Yamaguchi, Y., Doi, M., & Gosho, M. (2020) · Statistics in Medicine · doi:10.1002/sim.8474 · Cited by 6
“From formula (1), it is derived that yi marginally follows MVNni (Xiβ,Vi), where Vi = WiDW T i + Σi.”
BackgroundMethodInfluential
ASSOCIATION BETWEEN ANATOMICAL AND CLINICAL OUTCOMES OF NEOVASCULAR AGE-RELATED MACULAR DEGENERATION TREATED WITH ANTIVASCULAR ENDOTHELIAL GROWTH FACTOR
Nguyen, V., Puzo, M., Sánchez‐Monroy, J., Gabrielle, P., Creuzot-Garcher, C. P., Baudin, F., Wolff, B., Castelnovo, L., Michel, G., O’Toole, L., et al. (2020) · Retina · doi:10.1097/iae.0000000000003061 · Cited by 6
Controlled Trial Examining the Strength-Based Grit Wellbeing and Self-Regulation Program for Young People in Residential Settings for Substance Use
Quinn, C. A., Walter, Z. C., de Andrade, D., Dingle, G. A., Haslam, C., & Hides, L. M. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192113835 · Cited by 9
Walking speed is associated with postoperative pain catastrophizing in patients with lumbar spinal stenosis: a prospective observational study
Wada, T., Tanishima, S., Kitsuda, Y., Osaki, M., Nagashima, H., Noma, H., & Hagino, H. (2022) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-022-06086-y · Cited by 6
Long-Term Effects of Internet-Based Cognitive Behavioral Therapy on Depression Prevention Among University Students: Randomized Controlled Factorial Trial
Nakagami, Y., Uwatoko, T., Shimamoto, T., Sakata, M., Toyomoto, R., Yoshida, K., Luo, Y., Shiraishi, N., Tajika, A., Sahker, E., et al. (2024) · JMIR Mental Health · doi:10.2196/56691 · Cited by 5
“In addition, changes in PHQ-9, GAD-7, and CBT Skills Scale were repeatedly measured up to 52 weeks and analyzed with mixed models for repeated measures [23].”
Acceptability and efficacy of a smartphone application intervention for mental health care based on interpersonal psychotherapy for improving depression symptoms in prenatal women: Protocol for a randomized controlled trial
Toshishige, Y., Chatani, N., Kawasaki, S., Goto, S., Yoshida, Y., Takahashi, Y., Shimasaki, M., Okami, T., Sakaguchi, G., Furukawa, T. A., et al. (2025) · Internet Interventions · doi:10.1016/j.invent.2025.100838 · Cited by 5
“A mixed-effects repeated-measures (MMRM) analysis will be applied (Mallinckrodt et al., 2001), with the change in PHQ-9 scores from baseline as the response variable.”
The Effect of Different Types of Exercise on Sleep Quality and Architecture in Parkinson Disease: A Single-Blinded Randomized Clinical Trial Protocol
Cristini, J., Potvin‐Desrochers, A., Seo, F., Dagher, A., Postuma, R. B., Rosa‐Neto, P., Carrier, J., Amara, A. W., Steib, S., Paquette, C., et al. (2023) · Physical Therapy · doi:10.1093/ptj/pzad073 · Cited by 5
Comparison of Precision and Accuracy of Five Methods to Analyse Total Score Data
Wellhagen, G. J., Karlsson, M. O., & Kjellsson, M. C. (2020) · The AAPS Journal · doi:10.1208/s12248-020-00546-w · Cited by 5
Indiana Palliative Excellence in Alzheimer’s Care Efforts (IN-PEACE): Protocol for a randomized controlled trial in persons with advanced dementia
Holtz, L. R., Kroenke, K., Gao, S., Hickman, S. E., Torke, A. M., Johnson, N. M., Pemberton, A., Vrobel, A., Pan, M., & Sachs, G. A. (2023) · Contemporary Clinical Trials · doi:10.1016/j.cct.2023.107217 · Cited by 5
Evaluation of Overall Treatment Effect in MMRM
Song, T., Dong, Q., Sankoh, A. J., & Molenberghs, G. (2013) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2013.834918 · Cited by 5
“Under various scenarios of MNAR, simulation studies have shown that MMRM outperforms many of the traditional methods, including last observation carried forward (LOCF), in terms of bias reduction and control of the type I error rate (Mallinckrodt et al., 2001; Siddiqui et al., 2009).”
Method
Dose-Response Mixed Models for Repeated Measures – a New Method for Assessment of Dose-Response
Wellhagen, G. J., Hamrén, B., Kjellsson, M. C., & Åstrand, M. (2020) · Pharmaceutical Research · doi:10.1007/s11095-020-02882-0 · Cited by 5
School-based cognitive behavioural intervention programme for addressing anxiety in 10- to 11-year-olds using short classroom activities in Japan: a quasi-experimental study
Urao, Y., Yoshida, M., Sato, Y., & Shimizu, E. (2022) · BMC Psychiatry · doi:10.1186/s12888-022-04326-y · Cited by 12
Long-term safety of duloxetine during open-label compassionate use treatment of patients who completed previous duloxetine clinical trials
Pangallo, B. A., Zhang, Q., Desaiah, D., David, P., Detke, M. J., & Kennedy, S. H. (2010) · Current Medical Research and Opinion · doi:10.1185/03007995.2010.522157 · Cited by 5
Use of generalized estimating equations in a trial in influenza to explore treatment effects over time
Keene, O. N., Davis, R. L., & Koch, G. G. (2004) · Pharmaceutical Statistics · doi:10.1002/pst.141 · Cited by 5
Impact of Data Imputation Methodology on Pain Assessment over 24 Hours in a Randomized, Placebo-Controlled Study of Gabapentin Enacarbil in Patients with Neuropathic Pain Associated with Postherpetic Neuralgia
Calkins, A., Gudin, J., Gidal, B. E., Jaros, M. J., Kim, R., & Shang, G. Y. (2016) · Pain Medicine · doi:10.1093/pm/pnv072 · Cited by 5
Diet quality and season affect physiology and energetic priorities of captive Steller sea lions during and after periods of nutritional stress
du Dot, T. J. (2008) · Open Collections · doi:10.14288/1.0066271 · Cited by 5
Self-Organized Prediction-Classification- Superposition of Longitudinal Cognitive Decline in Alzheimer's Disease: An Application to Novel Clinical Research Methodology
Sato, H., Hanazawa, R., Suzuki, K., Hashizume, A., & Hirakawa, A. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3546020 · Cited by 4
Online eurythmy therapy for cancer-related fatigue: a prospective repeated-measures observational study exploring fatigue, stress, and mindfulness
Timm, E., Ko, Y. M., Hundhammer, T., Berlowitz, I., & Wolf, U. (2024) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2024.1472562 · Cited by 4
“…(Bell et al., 2013), which is generally difficult to rule out, but for which mixed-effect models are considered a method of choice, given their capacity to minimize dropout bias in longitudinal research with both random or non-random missingness (Mallinckrodt et al., 2001; Bell et al., 2013).”
Method
Optimal Powder Deposition Process to Develop a New Direct-Write Additive Manufacturing System
Chung, H., Lee, N., Ko, J., Lee, T., Lee, P.-H., & Choi, J. Y. (2019) · International Journal of Precision Engineering and Manufacturing · doi:10.1007/s12541-019-00129-6 · Cited by 4
An application of the mixed‐effects model and pattern mixture model to treatment groups with differential missingness suspected not‐missing‐at‐random
Gosho, M., & Maruo, K. (2020) · Pharmaceutical Statistics · doi:10.1002/pst.2058 · Cited by 4
“All parameters in (2) can also be estimated using the REML method in the same manner as MMRM analysis.”
BackgroundMethodInfluential
Comprehensive efficacy of ipragliflozin on various conditioned type 2 diabetes compared with dipeptidyl peptidase-4 inhibitors and with both agents, based on a real-world multicenter trial
Sawano, F., Kamei, N., Miyahara, M., Kobuke, K., Nakanishi, S., Nagano, C., Nojima, H., Maeda, S., Watanabe, H., Kishimoto, R., et al. (2021) · Diabetology International · doi:10.1007/s13340-021-00492-8 · Cited by 4
“The mixed effect models for repeated measures [6] was used to compare changes over time within each group (baseline vs 12 w, 24 w, 36 w, 52 w), and multiplicity was adjusted with the Dunnett method [7].”
Method
Comparison of postoperative analgesic effects of thoracic epidural analgesia and rectus sheath block in laparoscopic abdominal surgery: A randomized controlled noninferiority trial
Owada, Y., Murata, Y., Hamaguchi, Y., Yamada, K., Inomata, S., Ogawa, K., Ohara, Y., Akashi, Y., Enomoto, T., Maruo, K., et al. (2023) · Asian Journal of Endoscopic Surgery · doi:10.1111/ases.13180 · Cited by 4
“NRS scores at rest and on coughing were analyzed with the mixed effect models for repeated measures (MMRM) method.(13) Then, noninferiority would be declared if the 95% upper confidence limit of least square mean differences between groups (RSB-TEA) for the NRS score on coughing at 24 hours would be lower than one.”
Method
Impact of Differential Rates of Disease Progression in Amyloid-Positive Early Alzheimer's Disease: Findings from a Longitudinal Cohort Analysis
Chandler, J., Georgieva, M. V., Desai, U. S., Done, N., Gómez-Liévano, A., Ye, W., Zhao, A., Eid, D., Hilts, A., Kirson, N. Y., et al. (2024) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2024.28 · Cited by 4
“While no statistical technique can fully protect against attrition, longitudinal analysis using mixed-effects modeling has been shown to be robust to the presence of nonignorable data missingness in both observational studies and clinical trials (23, 24).”
THE EFFECTS OF MISSING DATA TREATMENT ON PERSON ABILITY ESTIMATES USING IRT MODELS
Enciso, S., & Mariel, S. (2016) · Cited by 4

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