README for Toolbox-Cognition-Normer

This script runs off of Python code which will require the download and installation of Python 2.7 (instructions below)



1. Firstly, make sure that both the Assessment Data� and ScoresAndDemographicsData� sheets are both correctly downloaded from the Toolbox website. For verification: 

- TheScoresAndDemographics sheets should have these first 7 columns consecutively, just to make sure:
	PIN, Age, Gender, Race, Ethnicity, Language, Education


- The first 4 columns for this sheet should be these to make sure:
	PIN, stcode, Assmnt, MdlOrdr

2. 

	- A download of a version of Python 2.7 is required. You can download it from here: https://www.python.org/downloads/
	- Make sure the version downloaded is the newest version of Python 2.7 (currently the option listed on the right). The most recent version of Python 2.7 is Python 2.7.11
	- Download and Install as directed

3. 

Open a command prompt/terminal window.
Navigate to the location where you have the toolboxnormer.py script
Execute the script by typing in toolboxnormer.py and hitting return.

A dialogue box asking you to select a file should appear. 

- Navigate to where the ScoresAndDemographics sheet is located. Always select the ScoresAndDemographics� sheet first! (Selecting the other first will lead to parsing errors giving you blank norms). Hit Open� in the dialogue box to select it when highlighted

- After the first sheet is selected, navigate to the AssessmentData� sheet and select that. Always select this sheet second!

The app will parse through the sheets and norm the data, from which it should be done in about 10-15 seconds (depending on size of data sheets). 

Within the same directory/folder as the initial �ScoresAndDemographics� sheet, there should be a new file with the previous filename and “_PROCESSED” appended at the end. This processed� sheet includes the normed calculations.


Assuming all the appropriate input data is present in the sheets per participant, the selected norms should be calculated. The columns are labeled and further column data is based on rising levels of scrutiny (for example, moving from Uncorrected Scaled Scores on the left to T-Scores moving further right).

If there are any issues with how your data is processed, you can email me at hnrcdata@ucsd.edu

Along with your email, please attach both the ScoresAndDemographics� and AssesmentData sheets so I can troubleshoot the problem fully.

Thank you