Encipher is Different.
SSRS has an effective approach that is turning heads in the industry.
- Our unique stepwise calibration methodology for choosing the calibration model that is most effective at reducing selection bias and total error in key study outcomes. This experimentally validated procedure adapts a guided-search algorithm that maximizes bias reduction in a cost-effective way.
- An expansive bank of topic-customizable non-demographic calibration items validated through rigorous experimentation. These items offer an alternative to “one-size-fits-all” weighting by tailoring calibration items to the study topic, improving the effectiveness of calibration and controlling selection bias in study outcomes.
Encipher Hybid
A Validated Methodology for Blending Probability and Nonprobability Samples
Encipher Hybrid is a unique and sophisticated method that leverages study-specific outcomes, advanced modeling techniques, and customized non-demographic measures to produce weighting margins that are optimized for reducing selection bias in key study outcomes.
Encipher Hybrid
Encipher Nonprob
Improving Weighting for Nonprobability-only Samples
When budgets or timelines do not permit the inclusion of even a small probability sample, the SSRS Encipher Nonprob solution can recover some of the benefits of a full hybrid design.
Encipher NonprobSSRS Encipher in Action
Case Studies and Presentations that Showcase Encipher
A Case Study in Adaptation and Using Hybrid Samples to Produce Estimates for Subgroups
Learn More About How Encipher Hybrid was Used
A Case Study in Using Our Hybrid Approach to Better Understand Perceptions of For-Profit Colleges
Learn More About How Encipher Hybrid was Used
Can one weight fit all? Adjusting Hybrid Samples for Subgroup Estimation
MAPOR 2022 Conference Presentation
