Journal: | Ingeniería industrial : actualidad y nuevas tendencias |
Database: | PERIÓDICA |
System number: | 000374504 |
ISSN: | 1856-8327 |
Authors: | Martínez Carlos M1 |
Institutions: | 1Universidad de Carabobo, Facultad de Ingeniería, Valencia, Carabobo. Venezuela |
Year: | 2013 |
Volumen: | 3 |
Number: | 10 |
Pages: | 105-114 |
Country: | Venezuela |
Language: | Español |
Document type: | Artículo |
Approach: | Experimental, aplicado |
Spanish abstract | Survival analysis provides useful statistical tools to study the occurrence of events such as epileptic seizures, viral diseases, malignant tumors, re-hospitalization of patients among others. This paper offers statistical tests of interest to epidemiologists, biostatisticians and other researchers interested in new methodologies to be applied in medicine and other related health research areas. The main objective is to propose a new procedure based on Bonferroni’s method to compare survival curves of population groups with recurrent events. Nonparametric comparison tests with recurrent events data are illustrated. The idea is applying this methodology with a sequential procedure controlling the error type I on multiple contrast tests. The hypothesis test is: H0: S1(z) = S2(z) = … = Sk(z), H1: At least one Sr(z) is different with r = 1, 2, ..., k. Where, Sr(z) is the survival curve of the rth group and its estimation is calculated by the Generalized Product Limit Estimator (GPLE or Kaplan-Meier estimator). The survival functions are estimated using R-language programs and counting processes |
English abstract | Survival analysis provides useful statistical tools to study the occurrence of events such as epileptic seizures, viral diseases, malignant tumors, re-hospitalization of patients among others. This paper offers statistical tests of interest to epidemiologists, biostatisticians and other researchers interested in new methodologies to be applied in medicine and other related health research areas. The main objective is to propose a new procedure based on Bonferroni’s method to compare survival curves of population groups with recurrent events. Nonparametric comparison tests with recurrent events data are illustrated. The idea is applying this methodology with a sequential procedure controlling the error type I on multiple contrast tests. The hypothesis test is: H0: S1(z) = S2(z) = … = Sk(z), H1: At least one Sr(z) is different with r = 1, 2, ..., k. Where, Sr(z) is the survival curve of the rth group and its estimation is calculated by the Generalized Product Limit Estimator (GPLE or Kaplan-Meier estimator). The survival functions are estimated using R-language programs and counting processes |
Disciplines: | Medicina, Matemáticas |
Keyword: | Salud pública, Estadísticas de salud, Epidemiología, Análisis de supervivencia, Eventos recurrentes, Pruebas estadísticas |
Keyword: | Medicine, Mathematics, Public health, Health statistics, Epidemiology, Survival analysis, Recurrent events, Statistical tests |
Full text: | Texto completo (Ver HTML) |