junos
|
23c3613c60
|
Analyze adherence:
Look at time differences between subsequent daytime EMA.
Look at the daily evening EMA proportion.
|
2021-06-11 20:28:24 +02:00 |
|
junos
|
f48e5469e0
|
Finish labelling EMA sessions and document classify_sessions_adherence function.
|
2021-06-11 14:50:14 +02:00 |
|
junos
|
371e755159
|
Identify unique sessions and assign status.
Use CONSTANT variables for these statuses.
|
2021-06-11 13:50:24 +02:00 |
|
junos
|
04c069af47
|
Take the evening EMA time question into account as non-answered session.
|
2021-06-09 17:29:42 +02:00 |
|
junos
|
d5cd76f05a
|
[WIP] Prepare a function to classify adherence and illustrate steps in Jupyter Notebook.
|
2021-06-07 19:33:44 +02:00 |
|
junos
|
35a7fa0bbc
|
Take device ID into consideration for grouping sessions.
|
2021-06-07 16:44:42 +02:00 |
|
junos
|
8306e99392
|
Explain the histogram better and explore long sessions.
|
2021-06-07 12:01:41 +02:00 |
|
junos
|
06c179f4dd
|
Explain traditional concordance approach.
|
2021-06-02 18:42:39 +02:00 |
|
junos
|
2da9a8f9e3
|
Study session ID in depth.
|
2021-06-02 18:35:00 +02:00 |
|
junos
|
5cb527986b
|
Look at the ESM data and test JSON expansion.
|
2021-06-01 12:10:42 +02:00 |