FreesearchR

Choose your data

Upload a file, get data directly from REDCap or use local or sample data.

Upload a file:

Browse...

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No file selected. You can choose between these file types: .csv, .tsv, .txt, .xls, .xlsx, .rds, .ods, .dta

REDCap server

Web address

Format should be either 'https://redcap.your.institution/' or 'https://your.institution/redcap/'

API token

The token is a string of 32 numbers and letters.

Please fill in web address and API token, then press 'Connect'.

Data import parameters

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Select fields/variables to import and click the funnel to apply optional filters

Please specify data to download, then press 'Import'.

Select a data source:

Select a dataset:

No data selected! Use a dataset from your environment or from the environment of a package.

Select variables for final import

Exclude incomplete variables:

At 0, only complete variables are included; at 100, all variables are included.

Manual selection:

Overview and filtering

Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.

Filter data types

Read more on how data types are defined.

Filter observations

Apply filter on observation

Subset, rename and convert variables

Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.). There are more advanced options to modify factor/categorical variables as well as create new factor from a continous variable or new variables with R code. At the bottom you can restore the original data. Please note that data modifications are applied before any filtering.

Select variables to keep (if none selected, all are kept), rename variables and labels, and convert variable type/class in the table above. Apply changes by clicking the button below.

Advanced data manipulation

Below options allow more advanced varaible manipulations.

Reorder the levels of factor/categorical variables.

Create factor/categorical variable from a continous variable (number/date/time).

Create a new variable based on an R-expression.

Compare modified data to original

Raw print of the original vs the modified data.

Original data:

Modified data:

Reset to original imported dataset. Careful! There is no un-doing.

Settings

Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.

Compare strata?

No Yes

Option to perform statistical comparisons between strata in baseline table.

Press 'Evaluate' to create the comparison table.

Settings

To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.

Correlation cut-off

Set the cut-off for considered 'highly correlated'.

Create plot

Only non-text variables are available for plotting. Go the "Data" to reclass data to plot.

Adjust settings, then press "Plot".

Download

Plot height (mm)

Plot width (mm)

File format

Download plot

We have collected a few notes on visualising data and details on the options included in FreesearchR: View notes in new tab

Regression

If none are selected, all are included.

Press 'Analyse' to create the regression model and after changing parameters.

Coefficients plot

Plot height (mm)

Plot width (mm)

File format

Download plot

Analysis validation

Report

Choose your favourite output file format for further work, and download, when the analyses are done.

Output format

Download report

Data

Choose your favourite output data format to download the modified data.

Data format

No metadata is saved when exporting to csv.

Download data

Code snippets

Below are the code bits used to create the final data set and the main analyses.

This can be used as a starting point for learning to code and for reproducibility.