Statistically characterizing intra- and inter-individual variability in children with Developmental Coordination...

Area of Science:

• Neuroscience
• Developmental Psychology
• Biostatistics

Background:

• Children with Developmental Coordination Disorder (DCD) exhibit significant motor skill variability.
• Accurate statistical characterization of this variability is crucial for understanding DCD's underlying mechanisms.

Purpose of the Study:

• To demonstrate the effectiveness of a random coefficient model (RCM) for analyzing motor skill variability in children with and without DCD.
• To contrast RCM with the general linear model (GLM) in detecting group differences and individual variability.

Main Methods:

• Analysis of sensorimotor adaptation task data from children with and without DCD.
• Application of a random coefficient model (RCM) to characterize intra- and inter-individual variability.
• Comparison of RCM results against a traditional general linear model (GLM).

Main Results:

• The RCM identified significant differences between children with and without DCD that were missed by the GLM.
• RCM successfully characterized individual change trajectories during the motor task.
• The RCM provided a more nuanced analysis of motor performance variability.

Conclusions:

• Random coefficient models offer a superior statistical approach for analyzing motor variability in DCD research.
• RCMs can reveal subtle group differences and individual performance patterns, enhancing our understanding of DCD.
• This method facilitates a deeper investigation into the behavioral heterogeneity observed in children with DCD.