The Seven Deadly Sins of Statistical Analysis

Kuzon, William M.; Urbanchek, Melanie G.; McCabe, Steven J.

doi:10.1097/00000637-199609000-00006

Cited by 197 publications

(133 citation statements)

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“…Many scholars make the case to treat Likert scales as ordinal data (e.g. Cohen et al, 2007;Keller, 2008;Kuzon et al, 1996), yet in practice results from Likert scales tend to be used as interval data. The underlying reason for the discussion of whether ratings should be treated as interval or ordinal data, lies in the analysis as ordinal data requires the use of non-parametric techniques (Keller,2008;Kuzon et al, 1996).…”

Section: Methodsmentioning

confidence: 99%

“…Cohen et al, 2007;Keller, 2008;Kuzon et al, 1996), yet in practice results from Likert scales tend to be used as interval data. The underlying reason for the discussion of whether ratings should be treated as interval or ordinal data, lies in the analysis as ordinal data requires the use of non-parametric techniques (Keller,2008;Kuzon et al, 1996). Bryman and Cramer (2005) suggest that with regard to sociological variables, like attitudes, ordinal data is routinely treated as interval data.…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, in order to use parametric techniques to analyse the data (Kuzon et al, 1996), the data needs to fulfil certain criteria (e.g. random sample, normally distributed, large sample size).…”

Section: Methodsmentioning

confidence: 99%

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Passenger perceptions of the green image associated with airlines

Mayer

Ryley

Gillingwater

2012

Journal of Transport Geography

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Environmental issues in air transport have grown in importance in recent years, and in response some airlines have been proactive to demonstrate their 'green' credentials. The aim of this paper is to identify air traveller perceptions of different airlines with regard to green image, and how passengers perceive different measures that airlines can introduce to reduce their environmental impact. The research is based on a large quantitative survey, of over 600 air travellers, conducted at Liverpool John Lennon Airport between April and July 2010. The data in this papers stems from a range of attitudinal statements on airlines, and measures that airlines could adopt to improve their environmental performance.When presented with a list of airlines, about half of respondents were able to differentiate between airlines based on environmental friendliness. The results show that low-cost airlines in general are not seen as more or less environmentally friendly than full service network airlines. Yet air travellers do indicate differences in the environmental image based on individual airlines. Furthermore, results vary depending on whether passengers had flown previously with a particular airline. Passengers also differentiate between measures that airlines can adopt to reduce the environmental impact of aviation. Using newer aircraft is seen as the most effective way to address the issue.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Passenger perceptions of the green image associated with airlines

Mayer

Ryley

Gillingwater

2012

Journal of Transport Geography

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“…The MF parameters that determine the shape (ds) and spread (cs) illustrate the vagueness associated with the estimates. Additionally, the problem with the scalelevel requirement for statistical analyses [1,2] does not exist within the fuzzy framework. This also simplifies the construction of standard norms of populations.…”

Section: Discussionmentioning

confidence: 99%

“…It is a common practice to disregard the fact that mathematical operations, such as multiplication or division, are not valid for ordinal data and: "Therein lies the sin: simply expressing ordinal data using integers does not justify the use of parametric statistics." [2](S. 266).…”

Section: Introductionmentioning

confidence: 99%

The Fuzziness of Verbal Response Scales:The STAI-T Questionnaire

Bocklisch¹,

Bocklisch²,

Krems³

2011

Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011)

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In this paper we used a two-step procedure for the numerical translation of verbal frequency expressions of the response scale of a questionnaire (STAI-T). In an empirical study, 70 participants estimated numerical equivalents for verbal frequency expressions, data was modeled, and fuzzy membership functions were calculated. Results show that the scale's visual arrangement does not influence the interpretation of the words' meanings. We argue that traditional statistics are inappropriate for the analysis of verbal response data and demonstrate the alternative of fuzzy analysis, providing an example.

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Statistical presentation and analysis of ordered categorical outcome data in rheumatology journals

LaValley

Felson

2002

Arthritis & Rheumatism

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Objective. To assess the appropriateness of presentation of summary measures and analysis of ordered categorical (ordinal) data in three rheumatology journals in 1999, and to consider differences between basic and clinical science articles. Methods. Six hundred forty-four full-length articles from the 1999 editions of 3 rheumatology journals were evaluated for inclusion of an ordinal outcome. Articles were classified as basic or clinical science, and the appropriateness of presentation and analysis of the ordinal outcome were assessed. Chi-square tests were used to evaluate difference in percentages. Results. Ordinal outcomes were identified in 175 (27.2%) of 644 articles. Only 69 (39.4%) had appropriate data presentation, and 111 (63.4%) had appropriate data analysis. Appropriate presentation was seen less commonly in the basic science rather than the clinical science articles, but differences in the occurrence of appropriate analysis were not seen. Conclusion.Ordinal data are common in rheumatology articles, but presentation usually does not conform to recommended guidelines. KEY WORDS. Ordinal; Summary statistics; Hypothesis tests; Estimation.Ordinal data are generated when observations are placed into ordered categories. Such data are often generated by scoring radiographs or histologic slides, or from evaluating questionnaire responses. Ordinal data contain more information than categorical data without ordering (nominal data), but do not contain as much information as continuously measured data. This makes presentation of summary measures and hypothesis testing with ordinal data challenging.Previous analyses of medical research articles have suggested that ordinal outcome data is often presented or analyzed in ways that do not account for either the ordering or the categorical structure of the data (1-3). This can lead to biased estimates and reduced ability (low power) to detect important effects. Ordinal variables may be dichotomized as being above or below a fixed cut-off value and treated as binary (0/1), but this combines different levels together and can sacrifice information from the original scale (1). Contingency table methods that are appropriate for unordered categorical data do not take advantage of ordering in the data, resulting in loss of information and difficulty in interpretation (1). Methods for continuous data, such as the mean, standard deviation, Student's ttest, and F test, make several assumptions (e.g., consistent spacing, symmetry, and normality of the data distribution) that are generally not satisfied by ordinal data. As noted by Altman and Bland, "Although some statistical methods, such as the t-test, are not sensitive to moderate departures from normality, it is generally preferable not to rely on this feature"(4).To use the order information in ordinal data, but to avoid unnecessary assumptions, biostatistics textbooks (5) and journal articles (1,3,4,6 -9) have recommended that nonparametric methods based on ranking the data be used. These methods include use of percentiles,...

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The Seven Deadly Sins of Statistical Analysis

Cited by 197 publications

References 0 publications

Passenger perceptions of the green image associated with airlines

Passenger perceptions of the green image associated with airlines

The Fuzziness of Verbal Response Scales:The STAI-T Questionnaire

Statistical presentation and analysis of ordered categorical outcome data in rheumatology journals

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