* Changes in the offline tool based upon the new released base article.
* Tool now available in two variants - one allowing entry of 'education' and 'occupation' as codes (1 to 7), other as scores (10 to 1)
* To avoid confusion, second variant is only available on specific request using feedback form right now.
Version 2.0 beta:
- Note: this version stands withdrawn due to new base article giving update of the SES scale
- Corrected a significant bug in the calculation through version 1.0 beta.
- Number of rows of data entry possible reduced from 5000 to 2000 (Note- for data sets more than 2000, either the data can be entered in batches of 2000 each, or email request for customized larger size spreadsheet tool).
- Size of the spreadsheet file reduced by nearly 60% (from >1.2 mb to just about 500 kb)
- Sheets in the spreadsheet have been made easier to scroll and move through.
- Instructions added for how to paste-special the output rather than paste, back to own master chart.
- Colored box (yellow highlighted) added to the sheet ‘DATA’ as a reminder for the necessary inputs before beginning data entry
- Colored box (yellow highlighted) added to the sheet ‘DATA’ as a reminder to ‘paste-special’ the output back, after data entry.
- Data entry validation (flagging of error) added for:
# Entry of total family income as codes rather than actual income
Version 1.0 beta:
- Note: this version stands withdrawn due to a significant bug
- What this tool adds:
- Added data entry validation (error flagging) for
# Beginning of data entry without first entering the CPI-IW value
# Beginning of data entry without first entering the number of participants (rows of data)
# Entry of blank data
# Entry of any number other than the valid codes
# Entry of alphanumeric data
# Entry of income as range rather than a single number
Why this tool?
The essence of calculating of the scale from the data entered is a ‘NESTED IF’ spreadsheet formula. So, why this tool is required?
It adds data validation for the data entered, before calculation of the scale is done.
Why is this important?
Just as an example, let us say that during data entry for a particular row of data, ‘occupation’ variable was erroneously missed and remained blank. If validation is not done, the scale would get calculated for that individual subject too and this would be an error (as the score for ‘occupation’ does not get factored in).
As a second hypothetical example, let us say the ‘education of head’ which was to be entered as ‘1’ got erroneously typed in as ‘11’. What will this result in? The Kuppuswamy score gets erroneously increased by 10 and the SES category may also get erroneously changed. This error would not get noticed unless (a) all entered data is manually scrutinized or (b) a validation flag is built-in.
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