title | make |
---|---|
Analysis for ipod craving study |
worksheet |
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<?xml version="1.0" encoding="UTF-8"?> | |
<!DOCTYPE plist PUBLIC "-//Apple Computer//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd"> | |
<plist version="1.0"> | |
<dict> | |
<key>name</key> | |
<string>Comments</string> | |
<key>scope</key> | |
<string>source.stata</string> | |
<key>settings</key> | |
<dict> |
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#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
""" | |
Steve | |
A simple pre-processor (the name is a play on Stata and Sweave, but this is | |
much less fancy than Sweave) which grabs chunks of stata code from a markup file | |
(e.g. latex or markdown) and runs this code using the Stata binary. |
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#!/usr/bin/python | |
""" | |
For example: | |
echo "di 2^2" | statpipe | |
. di 2^2 | |
4 |
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. tab2 WASCRAVING INCOMPLETE STARTEDCRAVING | |
-> tabulation of WASCRAVING by INCOMPLETE | |
| INCOMPLETE | |
WASCRAVING | 0 1 | Total | |
-----------+----------------------+---------- | |
0 | 368 0 | 368 | |
1 | 400 467 | 867 |
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Iteration 1: log likelihood = -886.08863 | |
Computing standard errors: | |
Mixed-effects ML regression Number of obs = 203 | |
Group variable: person Number of groups = 15 | |
Obs per group: min = 3 | |
avg = 13.5 | |
max = 22 |
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. gen STARTEDCRAVING = strength_0 == 0 & (strength_1 > 0 & strength_1 < .) | |
. gen WASCRAVING = strength_0 == 0 | |
. gen COMPLETE = WASCRAVING if strength_1 >= 0 & strength_1 < . | |
(632 missing values generated) | |
. | |
. tab2 WASCRAVING COMPLETE STARTEDCRAVING |
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--- | |
name: "Conseqences of asthma" | |
redirect_url: "/accounts/profile/" | |
success_message: "Thanks for taking part in this study. Your help is greatly appreciated." | |
--- | |
~~~{#are_you_male_or_female choiceset="female" type="likert"} | |
Are you male or female? | |
~~~ |