Calibrating Non-Probability Internet Samples with Probability Samples Using Early Adopter Characteristics

• Activity Number: 514
• Type: Contributed
• Date/Time: Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Survey Research Methods
• Author(s): Charles DiSogra*+ and J. Michael Dennis and Elisa Chan
• Companies: Knowledge Networks, Inc. and Knowledge Networks, Inc.
• Keywords: Calibration ; Web surveys ; Online panels ; Probability-based samples ; Opt-in samples ; Internet panels

Abstract

A representative study sample drawn from a probability-based Web panel, after post-stratification weighting, will reliably generalize to the population of interest. Due to finite panel size, however, there are instances of too few panel members to meet sample size requirements. In such situations, a supplemental sample from a non-probability opt-in Internet panel may be added. When both samples are profiled with questions on early adopter (EA) behavior, opt-in samples tend to proportionally have more EA characteristics compared to probability samples. Taking advantage of these EA differences, this paper describes a statistical technique for calibrating opt-in cases blended with probability-based cases. Using data from attitudinal variables in a probability-based sample (n=611) and an opt-in sample (n=750), a reduction in the average mean squared error from 3.8 to 1.8 can be achieved with