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1.
Biometrics ; 78(1): 238-247, 2022 03.
Article in English | MEDLINE | ID: mdl-33354761

ABSTRACT

When a ranking of institutions such as medical centers or universities is based on a numerical measure of performance provided with a standard error, confidence intervals (CIs) should be calculated to assess the uncertainty of these ranks. We present a novel method based on Tukey's honest significant difference test to construct simultaneous CIs for the true ranks. When all the true performances are equal, the probability of coverage of our method attains the nominal level. In case the true performance measures have no exact ties, our method is conservative. For this situation, we propose a rescaling method to the nominal level that results in shorter CIs while keeping control of the simultaneous coverage. We also show that a similar rescaling can be applied to correct a recently proposed Monte-Carlo based method, which is anticonservative. After rescaling, the two methods perform very similarly. However, the rescaling of the Monte-Carlo based method is computationally much more demanding and becomes infeasible when the number of institutions is larger than 30-50. We discuss another recently proposed method similar to ours based on simultaneous CIs for the true performance. We show that our method provides uniformly shorter CIs for the same confidence level. We illustrate the superiority of our new methods with a data analysis for travel time to work in the United States and on rankings of 64 hospitals in the Netherlands.


Subject(s)
Hospitals , Research Design , Confidence Intervals , Monte Carlo Method , Probability , United States
2.
Muscle Nerve ; 64(5): 576-584, 2021 11.
Article in English | MEDLINE | ID: mdl-34383334

ABSTRACT

INTRODUCTION/AIMS: Duchenne and Becker muscular dystrophies (DMD and BMD, respectively) are characterized by fat replacement of different skeletal muscles in a specific temporal order. Given the structural role of dystrophin in skeletal muscle mechanics, muscle architecture could be important in the progressive pathophysiology of muscle degeneration. Therefore, the aim of this study was to assess the role of muscle architecture in the progression of fat replacement in DMD and BMD. METHODS: We assessed the association between literature-based leg muscle architectural characteristics and muscle fat fraction from 22 DMD and 24 BMD patients. Dixon-based magnetic resonance imaging estimates of fat fractions at baseline and 12 (only DMD) and 24 months were related to fiber length and physiological cross-sectional area (PCSA) using age-controlled linear mixed modeling. RESULTS: DMD and BMD muscles with long fibers and BMD muscles with large PCSAs were associated with increased fat fraction. The effect of fiber length was stronger in muscles with larger PCSA. DISCUSSION: Muscle architecture may explain the pathophysiology of muscle degeneration in dystrophinopathies, in which proximal muscles with a larger mass (fiber length × PCSA) are more susceptible, confirming the clinical observation of a temporal proximal-to-distal progression. These results give more insight into the mechanical role in the pathophysiology of muscular dystrophies. Ultimately, this new information can be used to help support the selection of current and the development of future therapies.


Subject(s)
Muscular Dystrophy, Duchenne , Dystrophin , Humans , Leg , Magnetic Resonance Imaging/methods , Muscle, Skeletal
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