Small Samples and Ordered Logistic Regression: Does it Help to Collapse Categories of Outcome?

American Statistician

Volumn 57, Issue 3, 2003, Pages 155-160

  Murad, Havi ^a,d   Fleischman, Anat ^b   Sadetzki, Siegal ^a,b   Geyer, Orna ^c   Freedman, Laurence S ^d  

^a GERTNER INSTITUTE FOR EPIDEMIOLOGY AND HEALTH POLICY RESEARCH   (Israel)

^b TEL AVIV UNIVERSITY   (Israel)

^c CARMEL MEDICAL CENTER   (Israel)

^d BAR ILAN UNIVERSITY   (Israel)

Author keywords

Cumulative logit; Proportional odds model; Wald test

Indexed keywords

EID: 0041572911     PISSN: 00031305     EISSN: 15372731     Source Type: Journal    
DOI: 10.1198/0003130031892     Document Type: Article

References (18)

1. Agresti, A. (1984), Analysis of Ordinal Categorical Data, New York: Wiley.
2. Altman, D. G. (1991), PracticalStatisticsforMedicalResearch, London:Chap- man & Hall, pp. 248.
3. Ananth, C. V., and Kleinbaum, D. G. (1997), “Regression Models for Ordinal Responses: A Review of Methods and Applications,” International Journal ofEpidemiology, 26, 1323-1333.
4. Ashby, D., West, C. R., and Ames, D. (1989), “TheOrderedLogisticRegression Model in Psychiatry: Rising Prevalence of Dementia in Old People Homes,” Statisticsin Medicine, 8, 1317-1326.
5. Cytel Software Corp. (2000), LogXactUser’s Guide, Version4, Cambridge MA.
6. Faden, V. B., and Graubard, B. I. (2000), “Maternal Substanceuse During Pregnancy and Developmental Outcome at Age Three,” Journal of Substance Abuse, 12,329-340.
7. Feinberg, S. E. (1980), TheAnalysis ofCross-Classified CategoricalData (2nd ed.), Cambridge, MA: MIT Press.
8. Greenland, S. (1994), “Alternative Models for Ordinal Logistic Regression,” Statisticsin Medicine, 13, 1665-1677.
9. Harrell, F. E. (2000), RegressionModelingStrategies, New York: Springer.
10. Hauck, W. W., and Donner, A. (1977), “Wald’s Test as Applied to Hypotheses in Logit Analysis,” Journal oftheAmerican StatisticalAssociation, 72, 851-853.
11. Kumanyika, S. K., Landis, J. R., Matthews, Y. L., Weaver, S. L., Harlan, L. C., and Harlan, W. R. (1994), “Secular Trends in Blood Pressure Among Adult Blacks andWhites Aged 18-34 Years in Two Body Mass Index Strata, United States, 1960-1980,” American Journalof Epidemiology, 15, 141-154.
12. Manor, O., Matthews, S., and Power, C. (2000), “Dichotomous or Categorical Response? Analysing Self-Rated Health and Lifetime Social Class,” Interna-tionalJournalof Epidemiology, 29, 149-157.
13. McCullagh, P. (1980), “Regression Models for Ordinal Data” (with discussion), Journal of Royal Statistical Society, Ser. B, 42, 109-142.
14. McCusker, J., Bigelow, C., Stoddard, A. M., and Zorn, M. (1994), “Human Immunodeficiency Virus Type 1 Antibody Status and Changes in Risk Behavior Among Drug Users,” Annals of Epidemiology, 4, 466-471.
15. Peterson, B.L., and Harrell, F.E. (1988),“PartialProportionalOddsModels and the LOGIST Procedure,” paper presented at SAS Users Group International, Thirteenth Annual Conference, Orlando, FL.
16. Peterson, B.L., and Harrell, F.E. (1990), “Partial Proportional Odds Models for Ordinal Response Variables,” Applied Statistics, 39, 205-217.
17. SAS InstituteInc. (1999), SAS/STAT() User’sGuide, Version 8, Cary, NC: SAS Institute Inc.
18. Walker, S. H., and Duncan, D. B. (1967), “Estimation of the Probability of an Event as a Function of Several Independent Variables,” Biometrika, 54, 167-179.