Mixed model
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- Fundamentals of Hierarchical Linear and Multilevel Modeling 1 G
- Linear Mixed Models
- Mixed Models - General
- Mixed Models – Random Coefficients
- Snijders, Tom AB 'Fixed and Random Effects'
- A Mixed-Effects Multinomial Logistic Regression Model
- Nonlinear Mixed-Effects Models and Nonparametric Inference
- A Bayesian Approach to the Mixed-Effects Analysis of Accuracy Data in Repeated-Measures Designs ⇑ ⇑ Yin Song A, Farouk S
- Multilevel Mixed Linear Model Analysis Using Iterative Generalized Least Squares
- Hierarchical Logistic Regression Modeling with SAS GLIMMIX Jian Dai, Zhongmin Li, David Rocke University of California, Davis, CA
- Logistic Mixed Effects Models a GLMM for Binary Data Takes The
- Applied Linear and Nonlinear Mixed Models* Introduction Mixed-Effect
- Fitting Linear Mixed-Effects Models Using Lme4
- Mixed Models in R Using the Lme4 Package Part 6: Nonlinear Mixed Models
- Mixed Model Analysis of Variance
- Multilevel Mixed (Hierarchical) Models
- Applications of Mixed-Effects Models in Biostatistics Author(S): Robert D
- Linear Mixed-Effects Regression