On the Theory of Scales of Measurement.

By S. S. Stevens, H. A. Meyerhoff, W. Davis, I. Bacto-Agar. 1946

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In Statistics and Probability

Citations in the corpus

Measuring Data (2022, background): “…and Afro-Asiatic languages suggested that different terms for metric and measurement exist, yet the distinction between them is similarly blurred (Stevens, 1946) mathematical quantiﬁcation (e.g., Boslaugh and Watters (2008)), that they apply to objects and their properties (e.g., Campbell…”
The Science of Visual Data Communication: What Works (2021, background): “There are other types of data (Stevens, 1946) that are frequently shown in visualizations (Bertin, 1983; Mackinlay, 1986; Munzner, 2014).”
JASP: Graphical Statistical Software for Common Statistical Designs (2019, background): “Each column header contains an icon that represents the measurement level of the corresponding variable: nominal, ordinal, or continuous (Stevens 1946).”
Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data. (2016, background): “It is easily forgotten that the assumption of normality is almost always violated in the population, and that calculating rp on ordinal data, such as those obtained from Likert items, is not strictly permissible anyway (Stevens, 1946).”
The Analytic Hierarchy Process - An Exposition (2001, background): “Stevens (1968), when questioning why the measurement problem is often overlooked, observed that:”
Generation of an Interval Metric Scale to Measure Attitude (2014, background): “In the same tone, Stevens (1946) coined the idea of measurement as assigning numbers to items or events according to rule (Matheson, 2008; Michell, 1999).”
Usability: Lessons Learned … and Yet to Be Learned (2014, unknown): “Stevens’s levels of measurement have been very inﬂuential, appearing in numerous statistics textbooks and used to guide recommendations given to users of some statistical analysis programs (Velleman & Wilkinson, 1993).”
The Spatial Semantic Hierarchy (2000, background): “First, much spatial knowledge is qualitative rather than quantitative, meaning that continuous quantities are represented by descriptions that can be manipulated as nominal or ordinal quantities, rather than as interval or ratio quantities [92].”
Latent Variable Theory (2008, methodology): “The different levels of measurement as introduced by Stevens (1946) and refined in Krantz et al. (1971) can then be thought of as specifying the detail to which the variable structure is mapped in the data structure.”
Ordinal Measures for Iris Recognition (2009, background): “Stevens suggested four levels of measurements from coarse to fine: nominal, ordinal, interval, and ratio measures [21].”