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What does ignore missing variables, keep weights as defined mean?
Sometimes data in a score is missing. When you define a score, you can specify how the score should be calculated when data is not available.
One method for handling missing data in a score is to ignore those variables without data. Since the weight of the variable missing data is not distributed to the other variables in the score, the weights of the remaining variables do not change; thus, the sum of their weights is less than 100% (note that scores are lower if you ignore missing variables than if you reallocate weights to available variables; see "What does re-allocate weights to available variables mean?").
This concept is best illustrated with an example. Let's say you define an application score called "Application Score" which weights a credit applicant's PAYDEX® Score at 40%, Commercial Credit Score Percentile at 30%, and Years in Business at 30%.
Application Score
| Variable | Weight |
| PAYDEX® Score | 40% |
| CCS Percentile | 30% |
| Years in Business | 30% |
| Total Weight | 100% |
If Years in Business is not available, the weights of the remaining variables do not change.
| Variable | Weight | Reallocated Weight * (see note) |
| PAYDEX® Score | 40% | 40% |
| CCS Percentile | 30% | 30% |
| Years in Business | 30% | 0% |
| Total Weight | 100% | 70% |