A Strategy for Analysing Multiple Risk Factors with Application to Cervical Pain Syndrome

Abstract:

When studying the possible effects of several factors in a given disease, two major problems arise: (1) confounding, and (2) multiplicity of tests. Frequently, in order to cope with the problem of confounding factors, models with multiple explanatory variables are used. However, the correlation structure of the variables may be such that the corresponding tests have low power: in its extreme form this situation is coined by the term “multicollinearity”. As the problem of multiplicity is still relevant in these models, the interpretation of results is, in most cases, very hazardous. We propose a strategy - based on a tree structure of the variables - which provides a guide to the interpretation and controls the risk of erroneously rejecting null hypotheses. The strategy was applied to a study of cervical pain syndrome involving 990 subjects and 17 variables. Age, sex, head trauma, posture at work and psychological status were all found to be important risk factors.

Key-Words:

Cervical Pain Syndrome - Mathematical Modelling - Multicollinearity - Multiple Tests - Tree Structure

• REFERENCES

• 1 Box GEP. Use and abuse of regression. Technometrics 1966; 8: 625-9.
• 2 Copas JB. Regression, prediction and shrinkage. J R Statist Soc B. 1983; 45: 311-54.
• 3 Cox DR, Snell EJ. The choice of variables in observational studies. Appl Statist 1974; 23: 51-9.
• 4 Greenberg RS, Kleinbaum DG. Mathematical modeling strategies for the analysis of epidemiologic research. Ann Rev Public Health 1985; 6: 223-45.
• 5 Thomas DC, Siemiatycki J, Dewar R, Robins J, Goldberg M, Armstrong BG. The problem of multiple inference in studies designed to generate hypotheses. Am J Epidemiol 1985; 122: 1080-95.
• 6 Freedman DA. A note on screening regression equations. Am Statist 1983; 37: 152-5.
• 7 Cramer EM. Multicollinearity. In Kotz S, Johnson NL. eds Encyclopedia of Statistical Sciences . New York: Wiley and Sons; 1985
• 8 Mosteller F, Tukey JW. Data Analysis and Regression. . Addison-Wesley. 1977
• 9 Joreskog KG. Lisrel. In Kotz S, Johnson NL. ed Encyclopedia of Statistical Sciences . New York: Wiley and Sons; 1985
• 10 Dartigues JF, Henry P, Puymirat E, Commenges D, Peytour P. Prevalence and risk factors of cervical pain syndrome in a working population. Neuroepid 1988; 7: 99-105.
• 11 Fisher RA. The Design of Experiment . Oliver and Boyd. 1935
• 12 Miller RG. Simultaneous Statistical Inference . Heidelberg: Springer Verlag; 1976
• 13 McCullagh P, Neider JA. Generalized Linear Models . Chapman and Hall. 1983
• 14 Kalbfleisch JD, Prentice RL. The Analysis of Failure Time Data . New York: Wiley and Sons; 1980
• 15 Holm S. A simple sequentially rejective multiple test procedure. Scand J Statist 1979; 6: 65-70.
• 16 Schaffer J. Modified sequentially rejective multiple test procedures. J Am Stat Assoc 1986; 81: 826-31.
• 17 Bauer P, Hackl P, Hommel G, Sonnemann E. Multiple testing of pairs of one-sided hypotheses. Metrika 1986; 33: 121-7.
• 18 Gabriel KR. Simultaneous test procedures – some theory of multiple comparisons. Ann Math Statist 1969; 40: 224-50.
• 19 Hommel G. Multiple test procedures for arbitrary dependence structures. Metrika 1986; 33: 321-6.