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BACKGROUND & OBJECTIVES Decision-analytic modelling can inform healthcare resource allocation and reimbursement decision-making, with modelling approaches adapted from a variety of disciplines. The objective of this thesis was to investigate the evidence surrounding when each approach should be used when conducting health economic evaluations. METHODS Project 1: A systematic review identified selection criteria, referred to as factors, through an evaluation of existing decision frameworks that aimed to differentiate between models. Project 2: Employing the factors identified from Project 1, a systematic review explored the extent to which empirical cross-validation studies agree on the importance of each on its impact to model selection. Project 3: A decision tree evaluating the cost-effectiveness of two vaccination strategies in children was reconstructed as system dynamics and agent-based models and compared. Scenario analyses assessed the situations whereby the model’s results would be sensitive to or be better handled by a particular approach. RESULTS Project 1: Among the eight frameworks identified; each involved a different set of structural or practical factors. Disagreements emerged between frameworks in the classification of the structural features specific to each modelling approach. Project 2: Nine exercises have been conducted, mostly focused on the criteria of interactivity (i.e., static vs. dynamic) and population resolution (i.e., aggregate vs. individual). Aggregate- and individual-level models were found to produce similar results with a practical trade-off between validity and feasibility. In the presence of large indirect effects, dynamic and static models often produced disparate results. Project 3: When calibrated, all three approaches reached consistent findings. Adaptation away from base-case assumptions led to different quantitative results on which vaccination strategy would be most optimal. CONCLUSION Despite disagreement among the frameworks on how to recommend modelling approaches, consistent conclusions were observed in empirical cross-validation studies. More empirical evidence is therefore needed to improve one’s understanding of the impact of the remaining factors on model selection. / Dissertation / Doctor of Philosophy (PhD)

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"July 2002." Bibliography: leaves 119-126. !. Introduction -- 2. Preliminiaries -- 3. Genetic algorithms -- 4. Equilibria and stability in economic models -- 5. Stochastic representation of economic models -- 6. Two population models -- 7. Overview. The aim of this dissertation is to provide a mathematical foundation for the application of genetic algorithms to economic models.

"July 2002." / Bibliography: leaves 119-126. / xi, 126 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / The aim of this dissertation is to provide a mathematical foundation for the application of genetic algorithms to economic models. / Thesis (Ph.D.)--University of Adelaide, Dept. of Applied Mathematics, 2002

The Biomass Integrated Gasification Application Systems (BIGAS) consortium is a research group whose focus is on developing modern biomass gasification technology for New Zealand's wood industry. This thesis is undertaken under objective four of the BIGAS consortium, whose goal is to develop modelling tools for aiding in the design of pilot-scale gasification plant and for assessing the economic feasibility of gasification energy plant. This thesis presents a chemical equilibrium-based gasification model and an economic feasibility assessment of gasification energy plant. Chemical equilibrium is proven to accurately predict product gas composition for large scale, greater than one megawatt thermal, updraft gasification. However, chemical equilibrium does not perform as well for small scale, 100 to 150 kilowatt thermal, Fast Internally Circulating Fluidised Bed (FICFB) gasification. Chemical equilibrium provides a number of insights on how altering gasification parameters will affect the composition of the product gas and will provide a useful tool in the design of pilot-scale plant. The economic model gives a basis for judging the optimal process and the overall appeal of integrating biomass gasification-based heat and power plants into New Zealand's MDF industry. The model is what Gerrard (2000) defines as a 'study estimate' model which has a probable range of accuracy of ±20% to ±30%. The modelling results show that gasification-gas engine plants are economically appealing when sized to meet the internal electricity demands of an MDF plant. However, biomass gasification combined cycle plants (BIGCC) and gasificationgas turbine plants are proven to be uneconomic in the New Zealand context.