By default brightstat rounds the results to five and p-values to three decimal places. If you need more presicion, just click on the the result cell in the output table.
Brightstat lets you recode categorical variables, often coded as strings, into ascending numbers automatically. Just select 'Automatic Recode' in the 'Data Menu' and indicate the variables to be recoded. The old values will be stored as value labels for the new numeric variable.
Brightstat sample files
In the 'Data Menu' there is 'Load Sample Datafile' in the first column 'Data File'. There you'll find a list of sample files (including files for all examples on Brightstat's website). So you can start discovering Brightstat right away.
Brightstat has a built in calculator which allows you to compute new variables with existing ones. If you have measured the weight (in kg) and height (in meters) of n subjects you can easily compute the body mass index (BMI) for all subjects. If your variables are named 'weight' and 'height' the formula would be: _weight/_height^2.
The sample file 'BodyFat' contains the variables 'Weight' (pounds) and 'Height' (inches), so the formula for calculating the BMI needs some adjustment in that case: (_Weight*0.45359237)/(_Height*2.54/100)^2.
Note: In the formula a variable name is always preceded by an underscore '_'.
Editing your data
Brightstat is not intended to be a data editor. Small changes can be done without problems but be aware that editing your data in Brighstat's data window may be very time consuming, especially with larger data files.
It is strongly recommended to prepare your data for Brightstat before uploading it into the database. A period '.' will be treated as a missing value.
How to prepare your data for Brightstat
Set data filter
You can define a filter variable for your data. Analysis and graphs are then performed for selected cases only. Select 'Filter Data' from the menu and indicate which values of which variables should be included in the analysis.
Split your datafile
You can split your datafile using a categorical variable. All tests and/or graphs are then performed for the individual categories of the split variable. Select 'Split Data' from the menu and indicate one or more split variables.