Commit 09201fe0 authored by kartoffelsalat's avatar kartoffelsalat

format links in README

parent d7e9d930
......@@ -7,7 +7,7 @@ All source code is licensed under the [GNU General Public License v3.0](https://
# List Randomizer
The `randomizeList.py` python script creates pseudo-randomized copies of a list where each row denotes an experimental trial.
The [`randomizeList.py`](https://gitlab.com/tkluth/empirical-scripts/blob/master/randomizeList.py) python script creates pseudo-randomized copies of a list where each row denotes an experimental trial.
Currently, it ensures the following two constraints (hence pseudo-randomization):
1. among the first two items should be no critical item
......@@ -20,7 +20,8 @@ The input for the script is a list as `.csv` file with the following specificati
- tab-delimited
- quote strings with `"`
You probably want to adjust the 6 variables at the top of `randomizeList.py` and then start the script with
You probably want to adjust the 6 variables at the top of [`randomizeList.py`](https://gitlab.com/tkluth/empirical-scripts/blob/master/randomizeList.py) and then start the script with
```
python randomizeList.py
```
......@@ -29,9 +30,9 @@ If successful, the script saves files named `randomListX.csv` (where `X` is a un
# Log Gaze Plots from Fixation Reports
The file `plots_and_analysis.R` was used as teaching material in a course on psycholinguistical eye-tracking. The file `fixation_report_no_preview.txt` contains the collected eye tracking data (as stored by Data Viewer). The script contains several occurrences of variables and factors investigated in the specific study, especially in the beginning: Column names `prosody, condition, item, critical, balancing, list, image_file, sound_file, picP` and several columns named `np1on, np1off' etc. The `on` and `off` column names denote on- and offsets of the corresponding words. Obviously, you will need to adjust these lines to the logic of your study.
The file [`plots_and_analysis.R`](https://gitlab.com/tkluth/empirical-scripts/blob/master/plots_and_analysis.R) was used as teaching material in a course on psycholinguistical eye-tracking. The file [`fixation_report_no_preview.txt`](https://gitlab.com/tkluth/empirical-scripts/blob/master/fixation_report_no_preview.txt) contains the collected eye tracking data (as stored by Data Viewer). The script contains several occurrences of variables and factors investigated in the specific study, especially in the beginning: Column names `prosody, condition, item, critical, balancing, list, image_file, sound_file, picP` and several columns named `np1on, np1off` etc. The `on` and `off` column names denote on- and offsets of the corresponding words. Obviously, you will need to adjust these lines to the logic of your study.
Apart from that, the script is ready to go. Just execute one line after the other, read the comments to understand what's going on and you will soon see one ratio-of-proportions and one log-gaze plot.
# Bayesian Analysis of Eye Tracking Data from Fixation Reports
The second part of the file `plots_and_analysis.R` provides the source code for an example of a Bayesian regression analysis (with different models and a comparison to an NHST analysis) of the provided empirical data using the [R package brms](https://cran.r-project.org/web/packages/brms/index.html). Again, if you execute the code line by line and read the comments, you should see the outcome of this statistical analysis. Of course you will need to adapt the specific statistical models to your data and research question.
\ No newline at end of file
The second part of the file [`plots_and_analysis.R`](https://gitlab.com/tkluth/empirical-scripts/blob/master/plots_and_analysis.R) provides the source code for an example of a Bayesian regression analysis (with different models and a comparison to an NHST analysis) of the provided empirical data using the [R package brms](https://cran.r-project.org/web/packages/brms/index.html). Again, if you execute the code line by line and read the comments, you should see the outcome of this statistical analysis. Of course you will need to adapt the specific statistical models to your data and research question.
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