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This is so we can link up the data.
This is so we can get in a format ImpactEd are expecting.
This is inspired by Duncan's code.
This is so we can pivot wider without creating lists. Also, export to csv for sharing.
This is because the second script cannot call the first script (causes RStudio to abort). One suspects it is to do with Google Authorisation not being able to apply across scripts. Move function to separate script so it can be tested more easily and to modularise code.
This is so we can see how respondents answered over time.
This is so we can see how people have responded over time.
This is to show how the share of responses change between each month.
avisionh
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Jan 10, 2021
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| # no. of surveys they complete | ||
| n <- 4 | ||
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| # no. of levels (likert) | ||
| lvls <- list(1:5) | ||
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| l <- rep(x = lvls, n) | ||
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| # get no. of unique permutations | ||
| combos <- expand.grid(l) |
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Never got round to completing this so feel free to ignore.
Essentially, i wanted all the possible combinations that people can answer questions.
For instance:
- Jan -> 'Very likely', Feb -> 'Likely', Mar -> 'Likely', June -> 'Very likely'
- Jan -> 'Very likely', Feb -> 'Very likely', Mar -> 'Likely', June -> 'Likely'
- ...
Then i wanted to calculate the percentage of people who responded in these way out of all those who have responded. I would then visualise each response as a node and the percentages as values for the edges.
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Author
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Merging and closing as Owen seems happy with it. |
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Summary
This branch visualises the movement how students have responded to the wellbeing survey over time.
The main script to review in this branch is:
notebooks/longitudinal-tracking/analysis.RChecklists
General checks
docs/aqa/assumptions_caveats.md), if necessarydocsfolderProject-specific checks