Distribution of quality adjusted life expectancy: A systems approach

Statistical methods are developed which assess survival data for two attributes; (1) prolongation of life, (2) quality of life. Health state transition probabilities correspond to prolongation of life and are modeled as a discrete-time semi-Markov process. Imbedded within the sojourn time of a particular health state are the quality of life transitions. They reflect events which differentiate perceptions of pain and suffering over a fixed time period. Quality of life transition probabilities are derived from the assumptions of a simple Markov process. These probabilities depend on the health state currently occupied and the next health state to which a transition is made. Utilizing the two forms of attributes the model has the capability to estimate the distribution of expected quality adjusted life years (in addition to the distribution of expected survival times). The expected quality of life can also be estimated within the health state sojourn time making more flexible the assessment of utility preferences. The methods are demonstrated on a subset of follow-up data from the Beta Blocker Heart Attack Trial (BHAT). This model contains the structure necessary to make inferences when assessing a general survival problem with a two dimensional outcome. ^

The influence of contact pressure, moisture, and compression time on the performance of cotton anti-contamination clothing

The objectives of this research were (1) to study the effect of contact pressure, compression time, and liquid (moisture content of the fabric) on the transfer by sliding contact of non-fixed surface contamination to protective clothing constructed from uncoated, woven fabrics, (2) to study the effect of contact pressure, compression time, and liquid content on the subsequent penetration through the fabric, and (3) to determine if varying the type of contaminant changes the effect of contact pressure, compression time, and liquid content on the transfer by sliding contact and penetration of non-fixed surface contamination. ^ It was found that the combined influence of the liquid (moisture content of the fabric), load (contact pressure), compression time, and their interactions significantly influenced the penetration of all three test agents, sucrose- 14C, triolein-3H, and starch-14C through 100% cotton fabric. The combined influence of the statistically significant main effects and their interactions increased the penetration of triolein- 3H by 32,548%, sucrose-14C by 7,006%, and starch- 14C by 1,900%. ^