An Algorithm for Converting Ordinal Scale Measurement Data to Interval/Ratio Scale

Bibliographic Data

ID20282952
AuthorsJ Scott Granberg-Rademacker (Minnesota State University, Mankato, MN, USA,), J Scott Granberg‐rademacker (Minnesota State University, Mankato, corresponding author)
Year2010
Volume70
Issue1
Pages74-90
Publication date2010-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEducational and Psychological Measurement (JOURNAL)
Journal identifiersISSN: 0013-1644 • E-ISSN: 1552-3888
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/0013164409344532
OpenAlexW2123588333
LanguageEN
Citations received3
References cited34

The extensive use of survey instruments in the social sciences has long created debate and concern about validity of outcomes, especially among instruments that gather ordinal-level data. Ordinal-level survey measurement of concepts that could be measured at the interval or ratio level produce errors because respondents are forced to truncate or round off their responses to fit a given ordinal scale. This article presents a Markov chain Monte Carlo modeling technique that converts ordinal measurements to interval/ ratio. Simulated data demonstrate the robustness of this technique, and implications of this technique are discussed

Algorithm · Confidence interval · Econometrics · Geography · Interval (graph theory) · Level of measurement · Markov chain · Ordinal data · Ordinal optimization · Ordinal regression · Ordinal Scale · Robustness (evolution) · Scale (ratio) · Statistics · Survey data collection · Computer Science · Mathematics · Statistical Methods and Bayesian Inference

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