Description: This paper presents a statistical analysis of advanced age mortality data, using extreme value models to quantify the upper tail of the distribution of human life spans. From 2005 Living to 100 and Beyond Monograph, M-LI05-1.

Description: This paper presents an analysis of mortality in a sample of 441adults aged 55 to 85 at baseline, who were observed for eight years. The study was initiated for the purpose of analyzing age-related changes in a variety of physical variables and their impact on functional independence. The modeling approach is discussed and the factors which were most significantly related to mortality.

Description: Charts for An Extreme Value Analysis of Advanced age Mortality Data. From 2005 Living to 100 and Beyond Monograph, M-LI05-1.

Description: This paper presents an approach to analyzing continuing care retirement community CCRC data and demonstrates the methodology by using data from a CCRC. From The Old-Age Crisis - Actuarial Opportunities - The 1996 Bowles Symposium, M-RS99-1.

Description: This paper presents an approach to analyzing continuing care retirement community [CCRC] data, and demonstrates the methods using data from a large CCRC. It is assumed that residents make transitions among a number of states that represent the levels of care required by residents. There is randomness associated with both the transition times and the states entered at these times. The model is conveniently characterized in terms of transition intensity functions, which represent the instantaneous rates of transition between pairs of states.

Description: This paper presents a multi-state stochastic model for analyzing continuing care retirement community CCRC populations. The model considers CCRCs with a number of independent living units and a skilled nursing facility. Residents may transfer temporarily or permanently to this facility. It is assumed that units vacated by deaths, withdrawals or permanent transfers are immediately occupied by new residents. Transfers are modeled using a time-homogeneous Markov process. The paper provides some probabilistic results and some numerical results obtained using this model. Some important generalizations of the model are also briefly discussed.