Abstract:
Propensity scores have been suggested in previous literature as a method for weighting
volunteer web samples in survey research (APPOR, 2013; Couper, 2000; Duffy et al.,
2005; Lee, 2004; Lee, 2006; Lee & Valliant, 2009; Schonlau et al., 2007; Valliant &
Dever, 2011). However, researchers have been somewhat unclear on their methods of
building the propensity score model itself. Some researchers have suggested the use of
webographic variables, or attitudinal variables, in these models to account for differences
between Internet users and non-users beyond demographics, like differences in lifestyles
and opinions, but their effectiveness in decreasing the bias in unadjusted volunteer web
sample estimates is unclear. This study investigated the use of webographic variables in
the propensity score model when using propensity scores as a weighting method. Results
showed that including all demographics was important for decreasing bias in the
unadjusted estimate as well as including webographics that were related to having
Internet access or to the study variable in question.