Multivariate analysis Voorbeeldclausules

Multivariate analysis. After the prognostic significance of each parameter was determined by univariate analysis, assessment of the relative importance of the parameters in explaining the success rate of canine autotransplantation was established by multivariate logistic regression analysis. The multiple regression models were fitted using all parameters with p<0.25 on the univariate analysis and those thought to be important on logical and medical grounds. The model which fitted the best to the data contained three preoperative parameters as covariates (Table 6). The significant parameter in determining the success rate of autotransplantation was age at transplantation (p=0.0458). More specifically, the age at transplantation had a negative correlation with the success rate (OR, 0.98; CI: 0.96-0.99). The higher the age at transplantation, the lower the success rate (Figure 15). Other parameters were not significant, including root development (p=0.7730) and condition of the apex (p=0.5456).