CoChat
Sign Up
Cited by 286Psychometric Methodologies and TestingReliability and Agreement in MeasurementStatistical Methods and Applications

The DOI matches its Crossref record; 20 of the 22 references it cites were found in a registry or an index.

A Comparison of Parametric and Non-Parametric Methods Applied to a Likert Scale

Open access
Mircioiu, Constantin, Atkinson, Jeffrey·2017·Pharmacy
DOI 10.3390/pharmacy5020026PMC PMC5597151
Open this paper in CoChat — free accountOpen PDF

Abstract

A trenchant and passionate dispute over the use of parametric versus non-parametric methods for the analysis of Likert scale ordinal data has raged for the past eight decades. The answer is not a simple “yes” or “no” but is related to hypotheses, objectives, risks, and paradigms. In this paper, we took a pragmatic approach. We applied both types of methods to the analysis of actual Likert data on responses from different professional subgroups of European pharmacists regarding competencies for practice. Results obtained show that with “large” (>15) numbers of responses and similar (but clearly not normal) distributions from different subgroups, parametric and non-parametric analyses give in almost all cases the same significant or non-significant results for inter-subgroup comparisons. Parametric methods were more discriminant in the cases of non-similar conclusions. Considering that the largest differences in opinions occurred in the upper part of the 4-point Likert scale (ranks 3 “very important” and 4 “essential”), a “score analysis” based on this part of the data was undertaken. This transformation of the ordinal Likert data into binary scores produced a graphical representation that was visually easier to understand as differences were accentuated. In conclusion, in this case of Likert ordinal data with high response rates, restraining the analysis to non-parametric methods leads to a loss of information. The addition of parametric methods, graphical analysis, analysis of subsets, and transformation of data leads to more in-depth analyses.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/pharmacy5020026

Cites

20 of 20 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Distributions of ranking data (number of values/rank) for each of the 50 ranked competencies (lines). The four subgroups are as follows: community pharmacists (CP, n = 183 respondents, top left); hospital pharmacists (HP, n = 188, top right); industrial pharmacists (IP, n = 93, bottom right); pharmacists in other occupations such as regulatory affairs, consultancy, and wholesale (OP, n = 72, bottom left).
Figure 1 Distributions of ranking data (number of values/rank) for each of the 50 ranked competencies (lines). The four subgroups are as follows: community pharmacists (CP, n = 183 respondents, top left); hospital pharmacists (HP, n = 188, top right); industrial pharmacists (IP, n = 93, bottom right); pharmacists in other occupations such as regulatory affairs, consultancy, and wholesale (OP, n = 72, bottom left).CC BY · PubMed Central
Figure 2 Values for the difference Rank 4–Rank 3 for all four subgroups. The four subgroups are as follows: community pharmacists (CP, n = 183 respondents, green circles); hospital pharmacists (HP, n = 188, red squares); industrial pharmacists (IP, n = 93, blue triangles); pharmacists in other occupations such as regulatory affairs, consultancy, and wholesale (OP, n = 72, orange inverted triangles).
Figure 2 Values for the difference Rank 4–Rank 3 for all four subgroups. The four subgroups are as follows: community pharmacists (CP, n = 183 respondents, green circles); hospital pharmacists (HP, n = 188, red squares); industrial pharmacists (IP, n = 93, blue triangles); pharmacists in other occupations such as regulatory affairs, consultancy, and wholesale (OP, n = 72, orange inverted triangles).CC BY · PubMed Central
Figure 3 Graphic presentation of the data for the ranking of the 50 competencies. The four subgroups are as follows: community pharmacists (CP, n = 183 respondents, green circles), hospital pharmacists (HP, n = 188, red squares), industrial pharmacists (IP, n = 93, blue triangles), and pharmacists in other occupations such as regulatory affairs, consultancy, and wholesale (OP, n = 72, orange inverted triangles).
Figure 3 Graphic presentation of the data for the ranking of the 50 competencies. The four subgroups are as follows: community pharmacists (CP, n = 183 respondents, green circles), hospital pharmacists (HP, n = 188, red squares), industrial pharmacists (IP, n = 93, blue triangles), and pharmacists in other occupations such as regulatory affairs, consultancy, and wholesale (OP, n = 72, orange inverted triangles).CC BY · PubMed Central
Figure 4 Distributions of medians, means, and scores of ranks for competencies given by CP (same data as in Figure 3). (a): medians; (b): means; (c): scores.
Figure 4 Distributions of medians, means, and scores of ranks for competencies given by CP (same data as in Figure 3). (a): medians; (b): means; (c): scores.CC BY · PubMed Central
Figure 5 Correlation between the chi-square test and t-test for the competencies given in Table 5 in the comparison CP versus IP. (t-test = ((0.13 × chi-square) + 1.73), r2 = 0.91).
Figure 5 Correlation between the chi-square test and t-test for the competencies given in Table 5 in the comparison CP versus IP. (t-test = ((0.13 × chi-square) + 1.73), r2 = 0.91).CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

Sorted by citations

See all 286

Related

See all

Metadata

Authors
Mircioiu, C., & Atkinson, J.
Affiliations
  • Carol Davila University of Medicine and Pharmacy (RO)
  • Pharmacolor Consultants Nancy, 12 rue de Versigny, Villers 54600, France
Corresponding author
Atkinson, Jeffrey
ORCID
Atkinson, Jeffrey
Venue
Pharmacy
Publisher
MDPI AG
Published
2017-05-10
Volume
5
Issue
2
Pages
26
ISSN
2226-4787 (ISSN-L)
DOI
10.3390/pharmacy5020026
PMC
PMC5597151
OpenAlex
W2612879771
Cited by
286
References
22
Citations by year
2026: 28 · 2025: 34 · 2024: 37 · 2023: 44 · 2022: 51 · 2021: 48 · 2020: 24 · 2019: 11 · 2018: 6 · 2017: 2
FWCI
10.42
Type
journal article
Language
en
Open access
Licence
Locations
  • Pharmacy (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
European Commission
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords
Likert scale, ordinal data, pharmacists, professional competence, score analysis, subgroup comparison, data transformation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review