Risk factors of health conditions for old aged American people. A Comparison of Markov Based Logistic Model Determining the Risk Factors

      Аннотация: A number of statistical methods are available which are used to analyze categorical data with a broad scientific objective to describe the effect of certain risk factors on the evolution of event of interest. The objective of statistical modeling is to study the relationship between a dependent variable and some independent variables. This relationship can be used to identify the risk and prognostic factors of a specific disease as well as to predict the future disease status.Multi-state models are commonly used in studies of chronic disease, in which patients are assumed to pass through a series. Markov models are convenient and useful method of estimating transition rates between levels of categorical response variables, such as disease stages, which changes over time. Markov models are appropriate models for certain time series in which the observation at a given time are the category into which an individual falls. In recent years, Markov chain models are used in various fields because of its interesting properties to model longitudinal data and its exploratory power.Here I used it for health condition of Old aged american peoples. Hope it will help.

Ключевые слова: Comparison, Markov Based Logistic Model, Risk Factors of Health Conditions, Old Aged American People, Statistical analysis