Life table models, also known as mortality models or survival models, are statistical tools used to analyze and predict the mortality and survival patterns of a population or a specific group of individuals. These models are widely used in demography, actuarial science, epidemiology, and other fields to estimate life expectancy, evaluate public health interventions, and assess the impact of various factors on mortality rates.
A life table model consists of a set of mathematical equations and tables that summarize the survival experience of a population over a specific time period. In these models, individuals are grouped into different age categories, and their probabilities of survival and dying at each age interval are estimated based on observed mortality rates and population data.
Life table models typically incorporate various parameters such as age-specific mortality rates, life expectancy, and the probability of surviving to a certain age. The models can be further expanded to include additional factors, such as gender, socioeconomic status, or specific health conditions, to evaluate their influence on mortality rates.
These models play a crucial role in understanding the dynamics of human mortality and informing public health policies, retirement planning, and insurance pricing. By quantifying the risks and probabilities associated with mortality and survival, life table models provide valuable insights for decision-making processes and help individuals and organizations make informed choices related to mortality and life expectancy.
