Hybrid Samples & Non-Probability Calibration Tools

SSRS Hybrid Samples are a unique solution to maximizing data quality while placing a cap on rising costs. 

The idea of combining probability and non-probability survey data is a simple one, but combining it in such a way as to maximize quality while minimizing costs requires skillful statistical adjustment.

SSRS has developed an approach that utilizes data science to create a fully-customized solution to each unique application of hybridized data.

Hybrid Sample Advantages

SSRS uses machine learning tools to uncover the best metrics to adjust and blend the data together

SSRS has completed extensive testing on the blending of calibration techniques and methods to combine the samples

SSRS can provide recommendations as to the percent of data that should be probability and non-probability

If a survey of both non-probability and probability data is too costly, the SSRS Non-Probability Calibration approach is an excellent solution.


The SSRS Non-Probability Calibration approach utilizes our nationally representative probability RDD survey, the SSRS Omnibus, as well as other data sources, to attain key benchmarks chosen by SSRS methodologists to be most effective at reducing inherent bias in a given non-probability survey.


Questions used for calibration are chosen are chosen on a survey-by-survey basis and are topic-specific.  SSRS then applies interactive calibration targeting to minimize bias from the utilization of these benchmarks.


In numerous tests of  the SSRS Non-Probability Calibration approach, bias in the data has been reduced by as much as 90 percent.  Data reliability was maintained, and trended data remained consistent.

How can we help you design and execute your research?