Likert scales, levels of measurement and the "laws" of statistics

Advances in Health Sciences Education

Volumn 15, Issue 5, 2010, Pages 625-632

  Norman, Geoff ^a  

^a MCMASTER UNIVERSITY   (Canada)

Author keywords

ANOVA; Likert; Robustness; Statistics

Indexed keywords

ANALYSIS OF VARIANCE; ARTICLE; EDUCATION; FACTORIAL ANALYSIS; HUMAN; METHODOLOGY; REGRESSION ANALYSIS; SAMPLE SIZE; STATISTICS;

ANALYSIS OF VARIANCE; EDUCATIONAL MEASUREMENT; FACTOR ANALYSIS, STATISTICAL; HUMANS; REGRESSION ANALYSIS; SAMPLE SIZE; STATISTICS AS TOPIC;

EID: 78649906763     PISSN: 13824996     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10459-010-9222-y     Document Type: Article

References (19)

1. Bacchetti, P. (2002). Peer review of statistics in medical research: the other problem. British Medical Journal, 234, 1271-1273.
2. Berk, R. A. (1979). Generalizability of behavioral observations: a clarification of interobserver agreement and interobserver reliability. American Journal of Mental Deficiency., 83, 460-472.
3. Boneau, C. A. (1960). The effects of violations of assumptions underlying the t test. Psychological Bulletin, 57, 49-64.
4. Carifio, L., & Perla, R. (2008). Resolving the 50 year debate around using and misusing Likert scales. Medical Education, 42, 1150-1152.
5. Cohen, J. J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37-46.
6. Cohen, J. J. (1968). Weighted Kappa; Nominal scale agreement with provision for scaled disagreement or partial credit. Psychological Bulletin, 70, 213-220.
7. Cronbach, L. J. (1957). The two disciplines of scientific psychology. American Psychologist, 12, 671-684.
8. Dunlap, H. F. (1931). An empirical determination of means, standard deviations and correlation coefficients drawn form rectangular distributions. Annals of Mathematical Statistics, 2, 66-81.
9. Fleiss, J. L., & Cohen, J. J. (1973). The equivalence of weighed kappa and the intraclass correlation coefficient as measures of reliability. Educational and Psychological Measurement, 33, 613-619.
10. Fletcher, K. E., French, C. T., Corapi, K. M., Irwin, R. S. & Norman, G. R. (2010). Prospective measures provide more accurate assessments than retrospective measures of the minimal important difference in quality of life. Journal of Clinical Epidemiology (in press).
11. Gaito, J. (1980). Measurement scales and statistics: Resurgence of an old misconception. Psychological Bulletin, 87, 564-567.
12. Havlicek, L. L., & Peterson, N. L. (1976). Robustness of the Pearson correlation against violation of assumption. Perceptual and Motor Skills, 43, 1319-1334.
13. Hunter, J. E., & Schmidt, F. L. (1990). Dichotomozation of continuous variables: The implications for meta-analysis. Journal of Applied Psychology, 75, 334-349.
14. Jamieson, S. (2004). Likert scales: How to (ab)use them. Medical Education, 38, 1217-1218.
15. Kuzon, W. M., Urbanchek, M. G., & McCabe, S. (1996). The seven deadly sins of statistical analysis. Annals of Plastic Surgery, 37, 265-272.
16. Pearson, E. S. (1931). The analysis of variance in the case of non-normal variation. Biometrika, 23, 114-133.
17. Pearson, E. S. (1932a). The test of signficance for the correlation coefficient. Journal of the American Statistical Association, 27, 128-134.
18. Pearson, E. S. (1932b). The test of signficance for the correlation coefficient: Some further results. Journal of the American Statistical Association, 27, 424-426.
19. Suissa, S. (1991). Binary methods for continuous outcomes: a parametric alternative. Journal of Clinical Epidemiology, 44, 241-248.