In the interest of being a participatory citizen of the scientific community, here I offer some data analysis computer code that I have written for my own use, and that might be of use to others.
The Social Responsiveness Scale (SRS) is an instrument used in research and clinical care for individuals with autism spectrum disorder that was developed by John N. Constantino, MD.
As described by the publisher (WPS):
“This 65-item rating scale measures the severity of autism spectrum symptoms as they occur in natural social settings. Completed by a parent or teacher in just 15 to 20 minutes, the SRS provides a clear picture of a child’s social impairments, assessing social awareness, social information processing, capacity for reciprocal social communication, social anxiety/avoidance, and autistic preoccupations and traits. It is appropriate for use with children from 4 to 18 years of age.”
This GitHub repository contains code to score the 2005 Parent AutoScore version of the SRS (catalog #W-399AP at WPS) using IBM’s SPSS statistical program, generating final T Scores for individual cases from raw parent-reported responses.
For input, this code takes in the SPSS-formatted output from a REDCap database export.
For output, this code generates a final variable (i.e. srs_t_tot_calc) with a T Score for each case in the dataset.
This code will calculate a raw score based on individual item scores, but also allows for a manual (i.e. using the AutoScore form) raw score, and will check the two against each other for concordance.
This code expects some variables (i.e. sex, etc), which your database may not have; please consider this code as the starting point on which you can build. Most likely, you will need to modify this code to work for your particular dataset.
This code was written and tested using SPSS version 19. If you find an error, please let me know. Please use this code at your own risk. I can’t guarantee that I’ll be able to help you troubleshoot if a problem comes up.
A version of this code has been used in analysis of data that has been published after peer-review (i.e. here).
License: This is free and unencumbered software released into the public domain. Full license here. For more information, please refer to unlicense.org.
