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Using the GUI (1): Import Data and label columns
You can use the GUI to prepare data inputs for Linear Mixed Modeling in iMap4.
go to folder ./Data_Sample_with_codes/Data_sample_DEMO, and click Create Fixation Matrix on the Main window to start:
Click import data to import one or multiple files.
- One file
You can import either text files (.txt) or Matlab files (.mat)
- Text file (.txt)
You need to specify the number of columns and the delimitation of the file. Four delimitations are treated in this version: space, tabulation, comma and semicolon.
- Matlab file (.mat)
There should be only one matrix file within your .mat file
- Multiple files
You can import multiple files having the same number and type of columns. Moreover, all files should be either .txt or .mat but not a mixture of both.
Please note: To be able to proceed to next steps, it is mandatory to have at least Five columns in the file that refer to: Subject, Trial, horizontal fixation location X, vertical fixation location Y and the fixation Duration. Moreover, Trial index should be unique within a subject (i.e., all trails are represented by different number even they are not belonging to the same condition).
When you import one or multiple file(s), a pop-up window will ask you if Subject information is included in the selected file(s). If you answer no, a pop-up will appear for you to define subject manually. You need to select the files corresponding to the same subject by clicking on checkboxes.
In this step, you can rename the columns and create new predictor from existing predictors.
Column name could be changed here by manual input.
You can also import a .txt file with one column name on each line.
After clicking Continue, a pop-up will appear for creating new predictors
This is for the cases that user would like to create a categorical predictor from an existing continuous predictor. For example, the following screenshots show how to transfer Rating into a categorical predictor RatingCat:
Now you can proceed to the next step in the GUI: Parameters/Conditions
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