Applied Mixed Models in Medicine

Brown, Helen; Prescott, Robin

doi:10.1002/9781118778210

Cited by 284Statistical Methods and Bayesian InferenceStatistical Methods in Clinical TrialsSpatial and Panel Data Analysis

Applied Mixed Models in Medicine

Brown, Helen, Prescott, Robin·2014·Wiley eBooks

DOI 10.1002/9781118778210

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Random-effects models are the preferred methods for analysing clinical trial data.
“Random-effects models allow for estimation of between-person differences (ie, group effects) in within-person slopes (ie, change trajectories in secondary outcomes) and are the preferred methods for analysing clinical trial data.50”
From A mindfulness-based, cognitive, social, digital relapse-prevention intervention for youth with depression in Australia: study protocol for a randomised controlled trial of Rebound (2024) · cites this paper as [50]

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“Regression model assumptions were checked graphically using residual plots.(38) We performed multiple imputation using chained equations (multiple imputation by chained equations [MICE]) to account for missing data of height, weight, BMI, and shuttle run performance at follow-up.”
Method
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Self-citation
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“This analysis method takes into account all available data, performs better than alternatives when there are missing data, and estimates fixed effects while adjusting for correlation due to repeated measurements on each subject [77, 78].”
Method
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“For the primary outcome (EHP-30 pain scores at three years), a mixed effects linear regression model for repeated measures 17 calculated the adjusted difference between group means, along with 95% confidence intervals (CIs).”
Method
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“GLMM adjusts models for the random effects of repeated measuring on the same participants and can estimate both within- and between-subject variability.”
MethodInfluential
Weight loss relapse associated with exposure to perfluorinated alkylate substances
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“The model estimates mean outcome scores for each timepoint based on the available data, assuming that the participants consist of an a-select sample of a background population that we are interested in [40].”
Method
Psychosocial and Sociodemographic Contributors to Breastfeeding Intention in First-Time Mothers
Baumgartner, T., Bhamidipalli, S. S., Guise, D. M., Daggy, J., Parker, C. B., Westermann, M., Parry, S. I., Grobman, W. A., Mercer, B. M., Simhan, H. N., et al. (2020) · Maternal and Child Health Journal · doi:10.1007/s10995-020-02928-0 · Cited by 25 · see citing works
Surgical fixation compared with cast immobilisation for adults with a bicortical fracture of the scaphoid waist: the SWIFFT RCT
Dias, J. J., Brealey, S., Cook, L., Fairhurst, C. M., Hinde, S., Leighton, P. A., Choudhary, S., Costa, M. L., Hewitt, C. E., Hodgson, S., et al. (2020) · Health Technology Assessment · doi:10.3310/hta24520 · Cited by 27 · see citing works
Pilot study aiming to support sleep quality and duration during hospitalizations
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Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
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Aortic local biomechanical properties in ascending aortic aneurysms
Lin, S., Morgant, M., Marín-Castrillón, D. M., WALKER, P. M., Aho, S., Boucher, A., Presles, B., Bouchot, O., & Lalande, A. (2022) · Acta Biomaterialia · doi:10.1016/j.actbio.2022.06.019 · Cited by 23 · see citing works
The analysis of continuous data from n-of-1 trials using paired cycles: a simple tutorial
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Cork rings suggest how to manage Quercus suber to mitigate the effects of climate changes
Leite, C., Oliveira, V., Lauw, A., & Pereira, H. (2018) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2018.11.032 · Cited by 23 · see citing works
Income satisfaction is less predictive of life satisfaction in individuals who believe their lives have meaning or purpose: A 94-nation study
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The effects of loneliness on depressive symptoms among older adults during COVID-19: longitudinal analyses of the Canadian longitudinal study on aging
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Effect of a regular consumption of traditional and roasted oat and barley flakes on blood lipids and glucose metabolism–A randomized crossover trial
Reiners, S., Hebestreit, S., Wedekind, L., Kiehntopf, M., Klink, A., Rummler, S., Glei, M., Lorkowski, S., Schlörmann, W., & Dawczynski, C. (2023) · Frontiers in Nutrition · doi:10.3389/fnut.2023.1095245 · Cited by 26 · see citing works
Relationship between jumping to conclusions and clinical outcomes in people at clinical high-risk for psychosis
Catalán, A., Tognin, S., Kempton, M., Ståhl, D., de Pablo, G. S., Nelson, B., Pantelis, C., Riecher-Rössler, A., Bressan, R., Barrantes-Vidal, N., et al. (2020) · Psychological Medicine · doi:10.1017/s0033291720003396 · Cited by 16 · see citing works
Frequency of the T307A, N680S, and -29G>A single-nucleotide polymorphisms in the follicle-stimulating hormone receptor in Mexican subjects of Hispanic ancestry
García-Jiménez, G., Zariñán, T., Rodríguez‐Valentín, R., Mejía‐Domínguez, N. R., Gutiérrez‐Sagal, R., Hernández‐Montes, G., Tovar, A. R., Arechavaleta-Velasco, F., Canto, P., Granados, J., et al. (2018) · Reproductive Biology and Endocrinology · doi:10.1186/s12958-018-0420-4 · Cited by 21 · see citing works
Extending the I-squared statistic to describe treatment effect heterogeneity in cluster, multi-centre randomized trials and individual patient data meta-analysis
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“) and possibly across different settings (for example different geographies, or different centres).(2) In any realization of treatment effects across different groups the actual variation observed is a combination of “true” treatment effect variation and variation due to sampling error.”
Background
Assessment of retrospective collection of EQ-5D-5L in a US COVID-19 population
Sun, X., Fusco, M. D., Puzniak, L., et al. (2023) · Health and Quality of Life Outcomes · doi:10.1186/s12955-023-02187-x · Cited by 21 · see citing works
“A linear mixed model was used to characterize the relationship between EQ VAS and UI [10].”
Method
Distress-Based Gastrointestinal Symptom Clusters and Impact on Symptom Interference and Quality of Life in Patients with a Hematologic Malignancy Receiving Chemotherapy
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Authors: Brown, H., & Prescott, R.
ORCID: Prescott, Robin
Venue: Wiley eBooks
Publisher: Wiley
Published: 2014-12-12
DOI: 10.1002/9781118778210
OpenAlex: W2500762131
Cited by: 282
References: 0
Citations by year: 2026: 9 · 2025: 21 · 2024: 29 · 2023: 35 · 2022: 32 · 2021: 43 · 2020: 32 · 2019: 28 · 2018: 26 · 2017: 19 · 2016: 7 · 2015: 1
FWCI: 2.00
Type: book
Language: en
Open access: closed
Licence: doi.wiley.com/10.1002/tdm_license_1.1 (tdm)
Locations: Wiley eBooks (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
Keywords: mixed models, longitudinal data, repeated measures, random effects

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