new working version with major updates

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Andreas Gammelgaard Damsbo 2024-12-17 11:30:17 +01:00
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<title>freesearcheR platform documentation</title>
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<h1 class="title"><strong><em>freesearcheR</em></strong> platform documentation</h1>
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<h1 id="welcome">Welcome!</h1>
<p>So glad to see you here! Welcome to test this early concept of a platform to easily explore, manipulate and analyse clinical data.</p>
<p>Below will be a more detailed description of the included features and possibilities, as well as the planned and possible feature additions.</p>
<h2 id="contribute">Contribute</h2>
<p>Contributions are very welcome. If you find anything odd, or you think of features to add or remove, please <a href="https://github.com/agdamsbo/webResearch/issues">share and report on the project page on GitHub</a>.</p>
<h2 id="roadmap">Roadmap</h2>
<ul>
<li><p><label><input type="checkbox">Stratified analyses</label></p></li>
<li><p>Additional study designs:</p>
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<li><p><label><input type="checkbox" checked>Cross-sectional data analyses</label></p></li>
<li><p><label><input type="checkbox">Longitudinal data analyses</label></p></li>
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<li><p>More detailed variable browser</p>
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<li><p><label><input type="checkbox">Add histograms for data distribution</label></p></li>
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# Documentation on the freesearcheR platform
Welcome! So glad to see you here! Welcome to test this early concept of a platform to easily explore, manipulate and analyse clinical data.
Below will be a more detailed description of the included features and possibilities, as well as the planned and possible feature additions.
## Roadmap
- [ ] Stratified analyses
- Additional study designs:
- [x] Cross-sectional data analyses
- [ ] Longitudinal data analyses
- [ ] Survival analysis
- More detailed variable browser
- [ ] Add histograms for datadistribution
- [ ] Option to edit labels
- [ ] Plot regression analyses results
- [ ] Export modified data
- [ ] Include reproducible code for all steps
- [ ] Modify factor levels
- [ ] More options for date/datetime/time grouping/factoring

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---
title: "***freesearcheR*** platform documentation"
format:
html:
self-contained: true
minimal: true
---
# Welcome!
So glad to see you here! Welcome to test this early concept of a platform to easily explore, manipulate and analyse clinical data.
Below will be a more detailed description of the included features and possibilities, as well as the planned and possible feature additions.
## Contribute
Contributions are very welcome. If you find anything odd, or you think of features to add or remove, please [share and report on the project page on GitHub](https://github.com/agdamsbo/webResearch/issues).
## Roadmap
- [ ] Stratified analyses
- Additional study designs:
- [x] Cross-sectional data analyses
- [ ] Longitudinal data analyses
- [ ] Survival analysis
- More detailed variable browser
- [ ] Add histograms for data distribution
- [ ] Option to edit variable labels for nicer tables
- [ ] Plot regression analyses results
- [ ] Export modified data
- [ ] Include reproducible code for all steps
- [ ] Modify factor levels (including naming, order, collapsing, removing)
- [ ] More options for date/datetime/time grouping/factoring

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# Intro to webResearch/freesearcheR/VOICE
# Welcome
This is just placeholder text.
This is the ***freesearchR*** web data analysis tool. The ***freesearchR*** is an opinioated tool for easy data evaluation and analysis at the hands of the clinician. We intend it to be a powerful to, that is easy and secure to use.
By intention, this tool has been designed to be simple to use with a minimum of mandatory options to keep the workflow streamlined, while also including a few options to go even further.
There are four simple steps to go through:
1. Import data (this can be a spreadsheet on your machine or direct export from a REDCap server)
2. A *optional* step of data modification (change variable classes and creating categorical variables (factors) from numeric or time data)
3. Data analysis of cross-sectionally designed studies
- Classic baseline charactieristics (options to stratify and compare variables)
- Linear, dichotomous or ordinal logistic regression will be used depending on specified outcome variable
- Evaluation of model assumptions
4. Export the the analyses results as .docx or .odt.