Rescaling Ordinal Data to Interval Data in Educational Research

By Michael R. Harwell, Guido G. Gatti. 2001

186 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f28005b780ae7fa029dcd4a71dd2385cb73f0a61

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Equidistance of Likert-Type Scales and Validation of Inferential Methods Using Experiments and Simulations (2013, methodology): “To be able to use parametric statistics on ordinal data, several different methods for ‘rescaling’ ordinal scales to get interval properties have been proposed (e.g. Granberg-Rademacker, 2010; Wu, 2007; King et al., 2004; Harwell and Gatti, 2001; Bendixen and Sandler, 1995).”
Change-Supportive Employee Behavior: Antecedents and the Moderating Role of Time (2011, background): “Although the equality issue pertains to a general concern in survey research (e.g., Clogg & Shihadeh, 1994; Harwell & Gatti, 2001), the underlying problem is likely to be aggravated by the bipolar nature of the scale, as evidence suggests that negative and positive evaluative processes are…”
Item response theory and clinical measurement. (2009, background): “Some authors (Harwell & Gatti 2001, Kirisci et al. 2006, Mungas & Reed 2000) have made a similar suggestion (i.e., that trait scores are interval level) when items responses fit other IRT models.”
Using Likert Type Data in Social Science Research: Confusion, Issues and Challenges (2016, methodology): “Many statistical procedures used in educational and psychological research require the assumption of a normally distributed dependent variable, which presumed at least interval-level data (Harwell & Gatti, 2001 as cited in Shaftel, 2012).”
Generation of an Interval Metric Scale to Measure Attitude (2014, methodology): “Several researchers (Granberg-Rademacker, 2010; Harwell & Gatti, 2001; Hsu, Chang, & Hung, 2007; Wu, 2007) have approached the problem by rescaling Likert data using several methods in mathematical modeling.”
Can Likert Scales be Treated as Interval Scales?—A Simulation Study (2017, background): “Hodge and Gillespie (2007); Leung (2011) suggested increasing the number of points to 11 with empirical support, but the underlying metric of empirical data is always debatable.”
The Visual Analogue Scale for Rating, Ranking and Paired-Comparison (VAS-RRP): A new technique for psychological measurement (2018, methodology): “…issues with Likert-type scales To overcome the psychometric issues of Likert-type scales, several researchers (e.g., Granberg-Rademacker, 2010; Harwell & Gatti, 2001; Wu, 2007) have proposed transformation methods to scale ordinal Likert-type data before statistical estimation or hypothesis…”
Pursuing the elusive construct of distributed leadership (2015, background): “Sadly, raw scores do not necessarily satisfy the assumption of normality necessary in many statistical procedures and statistical results may be biased or spurious which threatens the validity of inferences (Harwell and Gatti, 2001; Zumbo and Zimmerman, 1993).”