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inst/apps/FreesearchR/www/intro.md
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# Welcome <img style="float: right;" src="FreesearchR-logo.png"> # Welcome <img style="float: right;" src="FreesearchR-logo.png">
This is the ***FreesearchR*** data analysis tool. We intend the ***FreesearchR*** to be a powerful and free tool for easy data evaluation and analysis at the hands of the clinician. If you need more advanced tools for regression models or plotting, you'll probably be better off using *R* or similar directly on your own machine. This is the ***FreesearchR*** data analysis tool. We intend ***FreesearchR*** to be a free tool for easy data evaluation and analysis. If you need more advanced tools, start with ***FreesearchR*** and then you'll probably be better off using *R* or similar directly.
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.
Here is a brief summary of the functions: Here is a brief summary of the functions:
1. Import data to get started. This can be a spreadsheet/file on your machine, direct export from a REDCap server, sample data or data from a your local environment if run locally. 1. **Import data** from a spreadsheet/file on your machine, direct export from a REDCap server, sample data or data from a your local environment if run locally.
1. Data inspection and modification (change variable classes, create new variables (categorical from numeric or time data, or completely new variables from the data) 1. **Data inspection** and **modification** like modifying variables or creating new (categorical from numeric or time data, or completely new variables from the data)
1. Evaluate data using descriptive analyses methods and inspect cross-correlations 1. **Evaluate data** using descriptive analyses methods and inspect cross-correlations
1. Create and export simple, clean plots for data overview and insights. 1. **Create and export simple, clean plots** for data overview and insights
1. Create regression models for even more advanced data analyses 1. **Create regression simple models** for even more advanced data analyses
- Linear, dichotomous or ordinal logistic regression will be used depending on specified outcome variable - Linear, dichotomous or ordinal logistic regression will be used depending on specified outcome variable
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- Evaluate model assumptions - Evaluate model assumptions
1. Export results 1. **Export results**
- Descriptive and regression analyses results for MS Word or [LibreOffice](https://www.libreoffice.org/) - Descriptive and regression analyses results for MS Word or [LibreOffice](https://www.libreoffice.org/)