Objective: Falls are a common problem facing elderly people and are associated with considerable mortality and morbidity. The objective of this paper is to study the application of the conditional model as an alternative for the statistical analysis of the occurrence of falls and their associated factors.
Methods: Cohort study. We select all ninety-eight residents admitted during the year 2007 in a long-term care centre, Seville, Spain. Five models were fitted: Negative binomial, standard Cox for the first fall, standard Cox for all falls, Andersen-Gill model, and Prentice-Williams-Peterson model.
Results: The crude incidence rate of falls was 26.3 per 100 person-months. The median time to fall decreases depending on the falls previously experienced, while the hazard rises. The AG's standard errors are between 1.4 and 2.7 times bigger than those estimated by Standard Cox. The major differences between marginal models were in the "Barthel 25-60" coefficient, where the conditional model attributed an HR=2.39 versus HR=3.77 estimated by the extension model.
Conclusion: As the risk increases depending on the falls previously suffered by an individual, the PWP-conditional model becomes an interesting alternative for obtaining unbiased and precise estimations of coefficients associated with possible risk factors of falls.