Structural equation models in survival analysis

Survival analysis is a collection of statistical methods developed to examine the time elapsed until a given event occurs. The fact that the exact time of occurrence of the event is not known is defined as a discrete-time survival analysis, whereas a clear determination of the event time is defined as a continuous-time survival analysis. Although Cox regression model is the most known continuous-time survival analysis model, parametric distributions can also be used. In addition to the observed variables, structural equation models have become a different method developed by adding hidden variables to analysis. Since the covariance relationship between the hidden and observed variables is based on the structural equation model, the fact that the margin of error is low has led to more reliable solution results. The effect of hidden variables that are not included in survival analysis has led to more comprehensive analyzes thanks to structural equation models. In addition, it is advantageous that discrete and continuous time separations, which are survival analysis approaches, can be used in structural equation models. In this study, detailed information about survival analysis, structural equation model and structural equation models in survival analysis is given. In order to demonstrate the applicability of structural equation models in survival analysis, it was applied and interpreted on the data set obtained from breastfeeding from 187 mothers of at least 6 months old infants who applied to Gazimağusa Medical Center Hospital Children's Polyclinics.