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Generalized Multi-linear Mixed Effects Model
2016Recently, many applications tend to find common and distinctive features from a group of datasets, of which distributions and structures are generally various. However, most existing methods can just cope with specific problems with fixed distributions and structures.
Chao Li 0013 +4 more
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Linear and generalized linear mixed effects models
2009In Chapter 8 we learned about the concept of hierarchical modeling, a data analysis approach that is appropriate when we have multiple measurements within each of several groups. In that chapter, variation in the data was represented with a between-group sampling model for group-specific means, in addition to a within-group sampling model to represent ...
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Using Generalized Linear (Mixed) Models in HCI
2016In HCI we often encounter dependent variables which are not (conditionally) normally distributed: we measure response-times, mouse-clicks, or the number of dialog steps it took a user to complete a task. Furthermore, we often encounter nested or grouped data; users are grouped within companies or institutes, or we obtain multiple observations within ...
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Consistent Estimators in Generalized Linear Mixed Models
Journal of the American Statistical Association, 1998Jiming Jiang
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Reliable Estimation of Generalized Linear Mixed Models using Adaptive Quadrature
The Stata Journal, 2002Sophia Rabe-Hesketh +2 more
exaly
Robust Analysis of Generalized Linear Mixed Models
Journal of the American Statistical Association, 2004Sanjoy K Sinha
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