Modeling the individual in Repeated Measures Models with ASCA+
When analyzing repeated measures designs—such as a patient’s evolution or a machine’s logs—an error in modeling the individual can lead to misleading conclusions, like false positives. To avoid this, ASCA+ correctly models individual variability, ensuring that results are robust, reliable, and reproducible, even with complex and unbalanced data.
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