Estimation of multi-state life table functions and their variability from complex survey data using the SPACE Program

The multistate life table (MSLT) model is an important demographic method to document life cycle processes. In this study, we present the SPACE (Stochastic Population Analysis for Complex Events) program to estimate MSLT functions and their sampling variability. It has several advantages over other programs, including the use of microsimulation and the bootstrap method to estimate the sampling variability. Simulation enables researchers to analyze a broader array of statistics than the deterministic approach, and may be especially advantageous in investigating distributions of MSLT functions. The bootstrap method takes sample design into account to correct the potential bias in variance estimates.bootstrap, health expectancy, multi-state life table, population aging

An extension of relational methods in mortality estimations

Actuaries and demographers have a long tradition of utilising collateral data to improve mortality estimates. Three main approaches have been used to accomplish the improvement- mortality laws, model life tables, and relational methods. The present paper introduces a regression model that incorporates all of the beneficial principles from each of these approaches. The model is demonstrated on mortality data pertaining to various groups of life insured people in Sweden.applied mathematics, collateral data, model life table, mortality law, relational method

Population Assessment During the Adult Stage of the Alfalfa Blotch Leafminer, \u3ci\u3eAgromyza Frontella\u3c/i\u3e (Diptera: Agromyzidae)

This paper presents a sampling procedure for estimating adult populations of the alfalfa blotch leafminer, Agromyza frontella (Rondani). The method is based on counts of the flies as they emerge from the soil following adult metamorphosis, taken in a series offurmel traps. Analysis of sampling variability showed that 80 traps per field will give adequate precision for life table studies in alfalfa. The pattern of counts was overdispersed but conformed to the negative binomial distribution

Significance of life table estimates for small populations: Simulation-based study of estimation errors

We study bias, standard errors, and distributions of characteristics of life tables for small populations. Theoretical considerations and simulations show that statistical efficiency of different methods is, above all, affected by the population size. Yet it is also significantly affected by the life table construction method and by a population’s age composition. Study results are presented in the form of ready-to-use tables and relations, which may be useful in assessing the significance of estimates and differences in life expectancy across time and space for the territories with a small population size, when standard errors of life expectancy estimates may be high.errors, life table, small populations