Recent years have witnessed the integration of theoretical advances in population genetics with large-scale analyses of complete genomes. As a result, a growing number of studies suggest the frequent occurrence of deleterious as well as adaptive mutations. Given the evidence for the widespread occurrence of selection, the finite sizes of natural populations, and the limited recombination in every genome, mutations under selection are expected to alter the fate of genetically linked mutations. The consequences of this non-independent behavior of mutations can be described by the Hill-Robertson effect in terms of the reduction in the effective population size (Ne). Reduction in the effective population size has two effects: 1) a reduction in levels of genetic variation and 2) a reduction in the effectiveness of selection that is manifested in an increased probability of fixation of deleterious mutations and a reduced probability of fixation of advantageous mutations. Changes in Ne that have previously been frequently associated with changes in recombination rate can also occur locally, in association with changes in the number of sites under selection even when the recombination rate remains uniform. The main objective of the work presented in this thesis is to investigate these local effects of the non-independent behavior of mutations on patterns of polymorphism and divergence in Drosophila using computer simulation and experimental approaches. A computer simulation approach is developed to investigate the local consequences of linked selection on estimates of selection and the proportion of adaptive substitutions using the McDonald-Kreitman framework. The results suggest that even a high level of recombination is unlikely to remove all the effects of linked selection. Ignoring these local linkage effects leads to misleading estimates of the intensity of selection and the proportion of adaptive substitutions. Two predictions of the Hill-Robertson effect were tested empirically by examining patterns of polymorphism and divergence combined with codon bias estimates in genes with and without introns: 1) the effectiveness of selection and polymorphism levels are expected to be reduced in the center of the long coding sequence of genes without introns (the intragenic Hill-Robertson effect), and 2) introns are expected to function as modifiers of recombination thereby increasing the effectiveness of selection in the central region of the coding sequence of genes containing centrally located introns. The evidence from divergence and codon bias patterns in genes with a long coding sequence supports the presence of the intragenic Hill-Robertson effect. However, polymorphism levels do not show the expected decrease in the center of the coding sequence. With regard to the second prediction, results indicate that intron presence does not increase the effectiveness of selection at synonymous sites in the set of investigated genes. Rather, intron presence is associated with increased levels of adaptation at nonsynonymous sites. Further investigations are necessary to clarify the role of introns in mediating the increase in adaptation.

This thesis explores the use of observational microdata in cost-effectiveness analysis. The application of econometric methods adjusting for selection bias is first reviewed and critically appraised in the economic evaluation literature using a structured template. Limitations of identified studies include lack of good quality evidence regarding the performance of different analytical approaches; inadequate assessment of the sensitivity of their results to violations of fundamental assumptions or variations to crucial estimator parameters; failure to combine the cost and effectiveness outcomes in a summary measure; and no consideration of stochastic uncertainty for the purpose of evaluating cost-effectiveness. Data from the Birthplace national cohort study are used in an attempt to address these limitations in the context of an empirical comparison of estimators relying on regression, matching, as well as the propensity score. It is argued that although these methods cannot address the potential impact of unobservable confounding, a novel approach to bias-corrected matching, combining entropy balancing with seemingly unrelated regression, still has the potential to offer important advantages in terms of analytical robustness. The net economic benefit is proposed as a straightforward way to exploit the strengths of rigorous econometric methodology in the development of reliable and informative cost-effectiveness analyses.