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. ^

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Use of a modified delphi process for establishing occupational exposure limits in support of health surveillance for space travelers

On-orbit exposures can come from numerous factors related to the space environment as evidenced by almost 50 years of environmental samples collected for water analysis, air analysis, radiation analysis, and physiologic parameters. For astronauts and spaceflight participants the occupational exposures can be very different from those experienced by workers performing similar tasks in workplaces on Earth, because the duration of the exposure could be continuous for very long orbital, and eventually interplanetary, missions. The establishment of long-term exposure standards is vital to controlling the quality of the spacecraft environment over long periods. NASA often needs to update and revise its prior exposure standards (Spacecrafts Maximum Allowable Concentrations (SMACs)). Traditional standards-setting processes are often lengthy, so a more rapid method to review and establish standards would be a substantial advancement in this area. This project investigates use of the Delphi method for this purpose. ^ In order to achieve the objectives of this study a modified Delphi methodology was tested in three trials executed by doctoral students and a panel of experts in disciplines related to occupational safety and health. During each test/trial modifications were made to the methodology. Prior to submission of the Delphi Questionnaire to the panel of experts a pilot study/trial was conducted using five doctoral students with the goals of testing and adjusting the Delphi questionnaire to improve comprehension, work out any procedural issues and evaluate the effectiveness of the questionnaire in drawing the desired responses. The remainder of the study consisted of two trials of the Modified Delphi process using 6 chemicals that currently have the potential of causing occupational exposures to NASA astronauts or spaceflight participants. To assist in setting Occupational Exposure Limits (OEL), the expert panel was established consisting of experts from academia, government and industry. Evidence was collected and used to create close-ended questionnaires which were submitted to the Delphi panel of experts for the establishment of OEL values for three chemicals from the list of six originally selected (trial 1). Once the first Delphi trial was completed, adjustments were made to the Delphi questionnaires and the process above was repeated with the remaining 3 chemicals (trial 2). ^ Results indicate that experience in occupational safety and health and with OEL methodologies can have a positive effect in minimizing the time experts take in completing this process. Based on the results of the questionnaires and comparison of the results with the SMAC already established by NASA, we conclude that use of the Delphi methodology is appropriate for use in the decision-making process for the selection of OELs.^

Bench-scale evaluation of the activated sludge process for treatment of a high -strength chemical plant wastewater

A bench-scale treatability study was conducted on a high-strength wastewater from a chemical plant to develop an alternative for the existing waste stabilization pond treatment system. The objective of this study was to determine the treatability of the wastewater by the activated sludge process and, if treatable, to determine appropriate operating conditions, and to evaluate the degradability of bis(2-chloroethyl)ether (Chlorex) and benzene in the activated sludge system. Four 4-L Plexi-glass, complete mixing, continuous flow activated sludge reactors were operated in parallel under different operating conditions over a 6-month period. The operating conditions examined were hydraulic retention time (HRT), sludge retention time (SRT), nutrient supplement, and Chlorex/benzene spikes. Generally the activated sludge system treating high-strength wastewater was stable under large variations of organic loading and operating conditions. At an HRT of 2 days, more than 90% removal efficiency with good sludge settleability was achieved when the organic loading was less than 0.4 g BOD$\sb5$/g MLVSS/d or 0.8 g COD/g MLVSS/d. At least 20 days of SRT was required to maintain steady operation. Phosphorus addition enhanced the performance of the system especially during stressed operation. On the average, removals of benzene and Chlorex were 73-86% and 37-65%, respectively. In addition, the low-strength wastewater was treatable by activated sludge process, showing more than 90% BOD removal at a HRT of 0.5 days. In general, the sludge had poor settling characteristics. The aerated lagoon process treating high-strength wastewater also provided significant organic reduction, but did not produce an acceptable effluent concentration. ^