Nominal, Ordinal, Interval, and Ratio Typologies are Misleading

Velleman, Paul F.; Wilkinson, Leland

doi:10.1080/00031305.1993.10475938

Cited by 301 publications

(170 citation statements)

References 23 publications

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“…Although it is recognised that there are arguments against using interval scales and parametric methods with ordinal data, a reasoned assignment of an interval scale to the ordinal categories here can generate a useful raw score measure and aid interpretation and communication of results in the context of the study (Baguley, 2009;Velleman & Wilkinson, 1993). We are concerned here with making judgements on quality improvements, and a scale that gives a stronger positive emphasis to a desired goal of "very good" (rather than just "good"), and a stronger negative emphasis to "very poor" (rather than just "poor") may be useful.…”

Section: Effect Sizementioning

confidence: 99%

I See What You Are Doing: Student Views on Lecturer Use of Tablet PCs in the Engineering Mathematics Classroom

Maclaren

Wilson

Klymchuk

2017

AJET

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Mathematically intensive engineering subjects at a tertiary level have traditionally been taught in classroom environments using whiteboards or blackboards. This paper reports on student views of the effectiveness of board and alternative technologies used within existing classroom contexts. Students in this study revealed a strong preference for the use of pen-enabled Tablet PCs as a delivery technology. The maintenance of a handwritten approach, combined with ready visibility of material, support for inclusion of other digital outputs and post-class access to material, were key factors influencing student preferences. Although this introduction of technology did not involve substantive changes in classroom pedagogical approaches, the study suggests that the Tablet PC technology may facilitate future development of more flexible approaches.

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Section: Effect Sizementioning

confidence: 99%

I See What You Are Doing: Student Views on Lecturer Use of Tablet PCs in the Engineering Mathematics Classroom

Maclaren

Wilson

Klymchuk

2017

AJET

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“…Furthermore, given the low number of participants and the strength of the repeated-measures ANCOVAs, we felt it would be better to proceed with the parametric analyses without eliminating those few, more extreme values. Parametric analyses were applied to the STAI, even though the data came from a Likert scale, given the simulations documenting the strength of this type of analysis when used with ordinal data (Velleman and Wilkinson, 1993;Davidson and Sharma, 1994;Stiger et al, 1998;Carifio and Perla, 2008;Norman, 2010). The homogeneity postulates for the regression slopes were respected [F(1.28) = 1.03 for heart rate, 1.23 for the STAI, all ns].…”

Section: D Studiomaxmentioning

confidence: 99%

Inducing an Anxiety Response Using a Contaminated Virtual Environment: Validation of a Therapeutic Tool for Obsessive–Compulsive Disorder

et al. 2016

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Obsessive-compulsive disorder (OCD) is characterized by the presence of unwanted and repetitive thoughts triggering significant anxiety, as well as the presence of ritual behaviors or mental acts carried out in response to obsessions to reduce the associated distress. In the contamination subtype, individuals are scared of germs and bacteria, are excessively concerned with cleaning, fear contamination and the spread of disease, and may have a very strong aversion to bodily secretions. A few studies on virtual reality (VR) have been conducted with people suffering from OCD, but they all focus on the subtype characterized by checking rituals. The goal of this study is to confirm the potential of a "contaminated" virtual environment in inducing anxiety in 12 adults suffering from contamination-subtype OCD compar ed to 20 adults without OCD (N = 32) using a within-between protocol. Subjective (questionnaire) and objective (heart rate) measurements were compiled. Participants were immersed in a control virtual environment (empty and clean room) and a "contaminated" virtual environment (filthy public restroom) designed for the treatment of OCD. Immersions were conducted in a 6-wall CAVE-like system. As hypothesized, the results of repeated-measures ANCOVAs revealed the significant impact of immersion in a filthy public restroom for participants suffering from OCD on both measures. Presence was correlated with anxiety in OCD participants and no difference in presence was observed between groups. Unwanted negative side effects induced by immersions in VR were higher in the OCD group. The clinical implications of the results and directions for further studies are discussed.

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“…Ever since its proposal Stevens' system has been criticized mainly for restricting the choice of statistical methods, leading to unnecessary resort to non-parametric methods, and that the taxonomy is too strict to apply to real-world data, instead of talking about meaningfulness (Velleman and Wilkinson 1993). For example, Mosteller (1977) argued for additional measurement levels such as Counted fractions , where measurements are bounded such that zero and one have specific meanings.…”

Section: Measurement and Representationmentioning

confidence: 99%

“…This is because we often find that the metric we have used is not optimal for a new hypothesis. According to Velleman and Wilkinson (1993):…”

Section: Turning Non-ordered Into Ordered Datamentioning

confidence: 99%

“…. [N]umbers do not have an innate scale; the scale derives from an understanding of the attribute that the numbers represent in the context of the question being asked, and new questions can arise after the numbers are assigned. (Velleman and Wilkinson 1993) We could, for example, think about what similarities and differences we find between the land cover categories 'Grassland', 'Pasture', and 'Deciduous Forest'. There are, among other things, aspects of the amount of vegetation, type of vegetation, and the naturalness that make these land cover categories similar or different.…”

Section: Turning Non-ordered Into Ordered Datamentioning

confidence: 99%

See 1 more Smart Citation

Categorical Measurement Semantics: A New Second Space for Geography

Ahlqvist

Ban

2007

Geography Compass

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Commonly used categorically or nominally measured data often portray each category as separate from other categories with no inherent ordering. Contrary to this portrayal and the perception that categorical data offer limited analytical capabilities, we examine the philosophical, cognitive, and practical basis for re‐thinking categorical measurements in terms of a second conceptual space for mapping out categorical semantics. The article presents a perspective that an inherent ordering of categories can be described through this space that provides a transformation into a numerical measurement domain. The article provides several examples of how geographic information analysis can benefit from adding this second conceptual space to the geographic data, together with a discussion of potential applications.

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Nominal, Ordinal, Interval, and Ratio Typologies are Misleading

Cited by 301 publications

References 23 publications

I See What You Are Doing: Student Views on Lecturer Use of Tablet PCs in the Engineering Mathematics Classroom

I See What You Are Doing: Student Views on Lecturer Use of Tablet PCs in the Engineering Mathematics Classroom

Inducing an Anxiety Response Using a Contaminated Virtual Environment: Validation of a Therapeutic Tool for Obsessive–Compulsive Disorder

Categorical Measurement Semantics: A New Second Space for Geography

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