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Opinion polls remain among the most efficient and widespread methods tocapture psycho-social data at large scales. However, there are limitations onthe logistics and structure of opinion polls that restrict the amount and typeof information that can be collected. As a consequence, data from opinion pollsare often reported in simple percentages and analyzed non-parametrically. Inthis paper, response data on just four questions from a national opinion pollwere used to demonstrate that a parametric scale can be constructed using itemresponse modeling approaches. Developing a parametric scale yieldsinterval-level measures which are more useful than the strictly ordinal-levelmeasures obtained from Likert-type scales common in opinion polls. The metricthat was developed in this paper, a measure of religious morality, can beprocessed and used in a wider range of statistical analyses compared toconventional approaches of simply reporting percentages at item-level. Finally,this paper reports the item parameters so that researchers can adopt theseitems to future instruments and place their own results on the same scale,thereby allowing responses from future samples to be compared to the resultsfrom the representative data in this paper.

Measuring religious morality using very limited poll responses: Implementing "big-data analytics" to small data