Sebastian Hellmann
@sehellmann.bsky.social
PostDoc working at TU Munich.
Interested in on computational modelling, decision-making, and confidence.
Cat owner, Ireland lover and brass music fan
Interested in on computational modelling, decision-making, and confidence.
Cat owner, Ireland lover and brass music fan
(e.g. the standard normal CDF) and normal distributions to fit the group-level distribution.
But we cannot simply apply the same transformation to the mean of the real-valued normal distribution to derive the group-level mean on the parameter scale! This ignores individual variability.
But we cannot simply apply the same transformation to the mean of the real-valued normal distribution to derive the group-level mean on the parameter scale! This ignores individual variability.
September 10, 2025 at 2:41 PM
(e.g. the standard normal CDF) and normal distributions to fit the group-level distribution.
But we cannot simply apply the same transformation to the mean of the real-valued normal distribution to derive the group-level mean on the parameter scale! This ignores individual variability.
But we cannot simply apply the same transformation to the mean of the real-valued normal distribution to derive the group-level mean on the parameter scale! This ignores individual variability.
If you’re estimating group-level means of constraint parameters, which are fitted with nonlinear transformations, beware that a common approach can produce biased estimates—especially with high individual variability.
For constraint parameters, we often use nonlinear transformations...
For constraint parameters, we often use nonlinear transformations...
September 10, 2025 at 2:41 PM
If you’re estimating group-level means of constraint parameters, which are fitted with nonlinear transformations, beware that a common approach can produce biased estimates—especially with high individual variability.
For constraint parameters, we often use nonlinear transformations...
For constraint parameters, we often use nonlinear transformations...