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Linear Mixed Models
iMap4 calls LinearMixedModel from Matlab for model estimations. You can find the relate concepts in Matlab help file:
Linear Mixed-Effects Models
This page explains the basic concept of Linear Mixed Model.
Estimating Parameters in Linear Mixed-Effects Models
This page explains the methods for estimating parameters in Matlab: Maximum likelihood estimation (ML) and Restricted maximum likelihood estimation (ReML).
Linear formula notation (Wilkinson Notation)
This page explains how to express your linear formula.
In a GLM setting,
y = Xβ + ε
only ε is the random effect:
This wiki is adapted from the original iMap4 guidebook.
If you have any questions about the iMap4 usage, please email [email protected]
Getting started
Theory
- Linear Mixed Models
- Pixel Wise Modeling and non-parametric statistics
- Family-wise error rate (FWER) under H0
- Power analysis of iMap4
Data structures and function usage
- Core functions
- Input Matrix
- LMMmap
- StatMap, Posthoc and figure outputs
- Other useful features and function
Example 1 (GUI)
- Background of Example 1
- Using the GUI (1): Import Data and label columns
- Using the GUI (2): Parameters and Conditions
- Using the GUI (3): Create smoothed fixation matrix
- Using the GUI (4): Optional for preprocessing
- Using the GUI (5): Descriptive Statistics Report
- Using the GUI (6): Spatial Mapping Using Linear Mixed Models
- Using the GUI (7): Hypothesis testing and Display results
- Using the GUI (8): Post-hoc analysis
Example 2 (Code)
Example 3 (Code)
Example 4 (Code)
Future development
Additional information