Journal ArticleDOI
Modern statistical methods for handling missing repeated measurements in obesity trial data: beyond LOCF.
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TLDR
The need for obesity trials, the assumptions that must be made regarding missing data in such trials, and some modern statistical methods for analysing data containing missing repeated measurements are reviewed.Abstract:
This paper brings together some modern statistical methods to address the problem of missing data in obesity trials with repeated measurements. Such missing data occur when subjects miss one or more follow-up visits, or drop out early from an obesity trial. A common approach to dealing with missing data because of dropout is 'last observation carried forward' (LOCF). This method, although intuitively appealing, requires restrictive assumptions to produce valid statistical conclusions. We review the need for obesity trials, the assumptions that must be made regarding missing data in such trials, and some modern statistical methods for analysing data containing missing repeated measurements. These modern methods have fewer limitations and less restrictive assumptions than required for LOCF. Moreover, their recent introduction into current releases of statistical software and textbooks makes them more readily available to the applied data analyses.read more
Citations
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Effect of Rimonabant, a Cannabinoid-1 Receptor Blocker, on Weight and Cardiometabolic Risk Factors in Overweight or Obese Patients: RIO-North America: A Randomized Controlled Trial
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Diets with High or Low Protein Content and Glycemic Index for Weight-Loss Maintenance
Thomas Meinert Larsen,Stine-Mathilde Dalskov,Marleen A. van Baak,Susan A. Jebb,Angeliki Papadaki,J. Alfredo Martínez,Teodora Handjieva-Darlenska,Mats Pihlsgård,Steen Stender,Claus Holst,Arne Astrup +10 more
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Efficacy and tolerability of rimonabant in overweight or obese patients with type 2 diabetes: a randomised controlled study
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Intra‐Articular Injection of Mesenchymal Stem Cells for the Treatment of Osteoarthritis of the Knee: A Proof‐of‐Concept Clinical Trial
Chris Hyunchul Jo,Young Gil Lee,Won Hyoung Shin,Hyang Sun Kim,Jee Won Chai,Eui Cheol Jeong,Ji Eun Kim,Hackjoon Shim,Ji Sun Shin,Il Seob Shin,Jeong Chan Ra,Sohee Oh,Kang Sup Yoon +12 more
TL;DR: Results showed that intra‐articular injection of 1.0 × 108 AD MSCs into the osteoarthritic knee improved function and pain of the knee joint without causing adverse events, and reduced cartilage defects by regeneration of hyaline‐like articular cartilage.
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The clinical efficacy of kinesio tape for shoulder pain: a randomized, double-blinded, clinical trial.
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References
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Book
Multiple imputation for nonresponse in surveys
TL;DR: In this article, a survey of drinking behavior among men of retirement age was conducted and the results showed that the majority of the participants reported that they did not receive any benefits from the Social Security Administration.
Book
Mixed-Effects Models in S and S-PLUS
TL;DR: Linear Mixed-Effects and Nonlinear Mixed-effects (NLME) models have been studied in the literature as mentioned in this paper, where the structure of grouped data has been used for fitting LME models.
Journal ArticleDOI
Random-effects models for longitudinal data
Nan M. Laird,James H. Ware +1 more
TL;DR: In this article, a unified approach to fitting two-stage random-effects models, based on a combination of empirical Bayes and maximum likelihood estimation of model parameters and using the EM algorithm, is discussed.
Journal ArticleDOI
Inference and missing data
TL;DR: In this article, it was shown that ignoring the process that causes missing data when making sampling distribution inferences about the parameter of the data, θ, is generally appropriate if and only if the missing data are missing at random and the observed data are observed at random, and then such inferences are generally conditional on the observed pattern of missing data.