Effect of echo time pair selection on quantitative analysis for adrenal tumor characterization with in-phase and opposed-phase MR imaging: initial experience

PURPOSE: To determine the effect of two pairs of echo times (TEs) for in-phase (IP) and opposed-phase (OP) 3.0-T magnetic resonance (MR) imaging on (a) quantitative analysis prospectively in a phantom study and (b) diagnostic accuracy retrospectively in a clinical study of adrenal tumors, with use of various reference standards in the clinical study. MATERIALS AND METHODS: A fat-saline phantom was used to perform IP and OP 3.0-T MR imaging for various fat fractions. The institutional review board approved this HIPAA-compliant study, with waiver of informed consent. Single-breath-hold IP and OP 3.0-T MR images in 21 patients (14 women, seven men; mean age, 63 years) with 23 adrenal tumors (16 adenomas, six metastases, one adrenocortical carcinoma) were reviewed. The MR protocol involved two acquisition schemes: In scheme A, the first OP echo (approximately 1.5-msec TE) and the second IP echo (approximately 4.9-msec TE) were acquired. In scheme B, the first IP echo (approximately 2.4-msec TE) and the third OP echo (approximately 5.8-msec TE) were acquired. Quantitative analysis was performed, and analysis of variance was used to test for differences between adenomas and nonadenomas. RESULTS: In the phantom study, scheme B did not enable discrimination among voxels that had small amounts of fat. In the clinical study, no overlap in signal intensity (SI) index values between adenomas and nonadenomas was seen (P < .05) with scheme A. However, with scheme B, no overlap in the adrenal gland SI-to-liver SI ratio between adenomas and nonadenomas was seen (P < .05). With scheme B, no overlap in adrenal gland SI index-to-liver SI index ratio between adenomas and nonadenomas was seen (P < .05). CONCLUSION: This initial experience indicates SI index is the most reliable parameter for characterization of adrenal tumors with 3.0-T MR imaging when obtaining OP echo before IP echo. When acquiring IP echo before OP echo, however, nonadenomas can be mistaken as adenomas with use of the SI index value.

Sixty-four-detector CT angiography of infrarenal aortic neck length and angulation: prospective analysis of interobserver variability

PURPOSE: To quantify the interobserver variability of abdominal aortic aneurysm (AAA) neck length and angulation measurements. MATERIALS AND METHODS: A total of 25 consecutive patients scheduled for endovascular AAA repair underwent follow-up 64-row computed tomographic (CT) angiography in 0.625-mm collimation. AAA neck length and angulation were determined by four blinded, independent readers. AAA neck length was defined as the longitudinal distance between the first transverse CT slice directly distal to the lowermost renal artery and the first transverse CT slice that showed at least a 15% larger outer aortic wall diameter versus the diameter measured directly below the lowermost renal artery. Infrarenal AAA neck angulation was defined as the true angle between the longitudinal axis of the proximal AAA neck and the longitudinal axis of the AAA lumen as analyzed on three-dimensional CT reconstructions. RESULTS: Mean deviation in aortic neck length determination was 32.3% and that in aortic neck angulation was 32.1%. Interobserver variability of aortic neck length and angulation measurements was considerable: in any reader combination, at least one measurement difference was outside the predefined limits of agreement. CONCLUSIONS: Assessment of the longitudinal extension and angulation of the infrarenal aortic neck is associated with substantial observer variability, even if measurement is carried out according to a standardized protocol. Further studies are mandatory to assess dedicated technical approaches to minimize variance in the determination of the longitudinal extension and angulation of the infrarenal aortic neck.

Pharmacogenetics-based population pharmacokinetic analysis of etravirine in HIV-1 infected individuals

Objectives: Etravirine (ETV) is metabolized by cytochrome P450 (CYP) 3A, 2C9, and 2C19. Metabolites are glucuronidated by uridine diphosphate glucuronosyltransferases (UGT). To identify the potential impact of genetic and non-genetic factors involved in ETV metabolism, we carried out a two-step pharmacogenetics-based population pharmacokinetic study in HIV-1 infected individuals. Materials and methods: The study population included 144 individuals contributing 289 ETV plasma concentrations and four individuals contributing 23 ETV plasma concentrations collected in a rich sampling design. Genetic variants [n=125 single-nucleotide polymorphisms (SNPs)] in 34 genes with a predicted role in ETV metabolism were selected. A first step population pharmacokinetic model included non-genetic and known genetic factors (seven SNPs in CYP2C, one SNP in CYP3A5) as covariates. Post-hoc individual ETV clearance (CL) was used in a second (discovery) step, in which the effect of the remaining 98 SNPs in CYP3A, P450 cytochrome oxidoreductase (POR), nuclear receptor genes, and UGTs was investigated. Results: A one-compartment model with zero-order absorption best characterized ETV pharmacokinetics. The average ETV CL was 41 (l/h) (CV 51.1%), the volume of distribution was 1325 l, and the mean absorption time was 1.2 h. The administration of darunavir/ritonavir or tenofovir was the only non-genetic covariate influencing ETV CL significantly, resulting in a 40% [95% confidence interval (CI): 13–69%] and a 42% (95% CI: 17–68%) increase in ETV CL, respectively. Carriers of rs4244285 (CYP2C19*2) had 23% (8–38%) lower ETV CL. Co-administered antiretroviral agents and genetic factors explained 16% of the variance in ETV concentrations. None of the SNPs in the discovery step influenced ETV CL. Conclusion: ETV concentrations are highly variable, and co-administered antiretroviral agents and genetic factors explained only a modest part of the interindividual variability in ETV elimination. Opposing effects of interacting drugs effectively abrogate genetic influences on ETV CL, and vice-versa.

A cladistic analysis of apolipoprotein B gene variation and plasma lipid and apolipoprotein B levels, using familial data

Any functionally important mutation is embedded in an evolutionary matrix of other mutations. Cladistic analysis, based on this, is a method of investigating gene effects using a haplotype phylogeny to define a set of tests which localize causal mutations to branches of the phylogeny. Previous implementations of cladistic analysis have not addressed the issue of analyzing data from related individuals, though in human studies, family data are usually needed to obtain unambiguous haplotypes. In this study, a method of cladistic analysis is described in which haplotype effects are parameterized in a linear model which accounts for familial correlations. The method was used to study the effect of apolipoprotein (Apo) B gene variation on total-, LDL-, and HDL-cholesterol, triglyceride, and Apo B levels in 121 French families. Five polymorphisms defined Apo B haplotypes: the signal peptide Insertion/deletion, Bsp 1286I, XbaI, MspI, and EcoRI. Eleven haplotypes were found, and a haplotype phylogeny was constructed and used to define a set of tests of haplotype effects on lipid and apo B levels.^ This new method of cladistic analysis, the parametric method, found significant effects for single haplotypes for all variables. For HDL-cholesterol, 3 clusters of evolutionarily-related haplotypes affecting levels were found. Haplotype effects accounted for about 10% of the genetic variance of triglyceride and HDL-cholesterol levels. The results of the parametric method were compared to those of a method of cladistic analysis based on permutational testing. The permutational method detected fewer haplotype effects, even when modified to account for correlations within families. Simulation studies exploring these differences found evidence of systematic errors in the permutational method due to the process by which haplotype groups were selected for testing.^ The applicability of cladistic analysis to human data was shown. The parametric method is suggested as an improvement over the permutational method. This study has identified candidate haplotypes for sequence comparisons in order to locate the functional mutations in the Apo B gene which may influence plasma lipid levels. ^

Cost and power analysis of linkage disequilibrium methods for locating genes influencing quantitative traits in humans

Linkage disequilibrium methods can be used to find genes influencing quantitative trait variation in humans. Linkage disequilibrium methods can require smaller sample sizes than linkage equilibrium methods, such as the variance component approach to find loci with a specific effect size. The increase in power is at the expense of requiring more markers to be typed to scan the entire genome. This thesis compares different linkage disequilibrium methods to determine which factors influence the power to detect disequilibrium. The costs of disequilibrium and equilibrium tests were compared to determine whether the savings in phenotyping costs when using disequilibrium methods outweigh the additional genotyping costs.^ Nine linkage disequilibrium tests were examined by simulation. Five tests involve selecting isolated unrelated individuals while four involved the selection of parent child trios (TDT). All nine tests were found to be able to identify disequilibrium with the correct significance level in Hardy-Weinberg populations. Increasing linked genetic variance and trait allele frequency were found to increase the power to detect disequilibrium, while increasing the number of generations and distance between marker and trait loci decreased the power to detect disequilibrium. Discordant sampling was used for several of the tests. It was found that the more stringent the sampling, the greater the power to detect disequilibrium in a sample of given size. The power to detect disequilibrium was not affected by the presence of polygenic effects.^ When the trait locus had more than two trait alleles, the power of the tests maximized to less than one. For the simulation methods used here, when there were more than two-trait alleles there was a probability equal to 1-heterozygosity of the marker locus that both trait alleles were in disequilibrium with the same marker allele, resulting in the marker being uninformative for disequilibrium.^ The five tests using isolated unrelated individuals were found to have excess error rates when there was disequilibrium due to population admixture. Increased error rates also resulted from increased unlinked major gene effects, discordant trait allele frequency, and increased disequilibrium. Polygenic effects did not affect the error rates. The TDT, Transmission Disequilibrium Test, based tests were not liable to any increase in error rates.^ For all sample ascertainment costs, for recent mutations ($<$100 generations) linkage disequilibrium tests were less expensive than the variance component test to carry out. Candidate gene scans saved even more money. The use of recently admixed populations also decreased the cost of performing a linkage disequilibrium test. ^

A Global Trend towards Democratic Convergence? A Lijphartian Analysis of Advanced Democracies.

The article offers a systematic analysis of the comparative trajectory of international democratic change. In particular, it focuses on the resulting convergence or divergence of political systems, borrowing from the literatures on institutional change and policy convergence. To this end, political-institutional data in line with Arend Lijphart’s (1999, 2012) empirical theory of democracy for 24 developed democracies between 1945 and 2010 are analyzed. Heteroscedastic multilevel models allow for directly modeling the development of the variance of types of democracy over time, revealing information about convergence, and adding substantial explanations. The findings indicate that there has been a trend away from extreme types of democracy in single cases, but no unconditional trend of convergence can be observed. However, there are conditional processes of convergence. In particular, economic globalization and the domestic veto structure interactively influence democratic convergence.

A fixed-links modeling approach to assess individual differences in the attentional blink: Analysis of behavioral and psychophysiological data

The attentional blink (AB) is a fundamental limitation of the ability to select relevant information from irrelevant information. It can be observed with the detection rate in an AB task as well as with the corresponding P300 amplitude of the event-related potential. In previous research, however, correlations between these two levels of observation were weak and rather inconsistent. A possible explanation of this finding might be that multiple processes underlie the AB and, thus, obscure a possible relationship between AB-related detection rate and the corresponding P300 amplitude. The present study investigated this assumption by applying a fixed-links modeling approach to represent behavioral individual differences in the AB as a latent variable. Concurrently, this approach enabled us to control for additional sources of variance in AB performance by deriving two additional latent variables. The correlation between the latent variable reflecting behavioral individual differences in AB magnitude and a corresponding latent variable derived from the P300 amplitude was high (r=.70). Furthermore, this correlation was considerably stronger than the correlations of other behavioral measures of the AB magnitude with their psychophysiological counterparts (all rs<.40). Our findings clearly indicate that the systematic disentangling of various sources of variance by utilizing the fixed-links modeling approach is a promising tool to investigate behavioral individual differences in the AB and possible psychophysiological correlates of these individual differences.

Survival analysis of longevity in siblings

Do siblings of centenarians tend to have longer life spans? To answer this question, life spans of 184 siblings for 42 centenarians have been evaluated. Two important questions have been addressed in analyzing the sibling data. First, a standard needs to be established, to which the life spans of 184 siblings are compared. In this report, an external reference population is constructed from the U.S. life tables. Its estimated mortality rates are treated as baseline hazards from which the relative mortality of the siblings are estimated. Second, the standard survival models which assume independent observations are invalid when correlation within family exists, underestimating the true variance. Methods that allow correlations are illustrated by three different methods. First, the cumulative relative excess mortality between siblings and their comparison group is calculated and used as an effective graphic tool, along with the Product Limit estimator of the survival function. The variance estimator of the cumulative relative excess mortality is adjusted for the potential within family correlation using Taylor linearization approach. Second, approaches that adjust for the inflated variance are examined. They are adjusted one-sample log-rank test using design effect originally proposed by Rao and Scott in the correlated binomial or Poisson distribution setting and the robust variance estimator derived from the log-likelihood function of a multiplicative model. Nether of these two approaches provide correlation estimate within families, but the comparison with the comparison with the standard remains valid under dependence. Last, using the frailty model concept, the multiplicative model, where the baseline hazards are known, is extended by adding a random frailty term that is based on the positive stable or the gamma distribution. Comparisons between the two frailty distributions are performed by simulation. Based on the results from various approaches, it is concluded that the siblings of centenarians had significant lower mortality rates as compared to their cohorts. The frailty models also indicate significant correlations between the life spans of the siblings. ^

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

Cost analysis of opt-in consent procedures for the Texas statewide immunization information system, ImmTrac

Background. Childhood immunization programs have dramatically reduced the morbidity and mortality associated with vaccine-preventable diseases. Proper documentation of immunizations that have been administered is essential to prevent duplicate immunization of children. To help improve documentation, immunization information systems (IISs) have been developed. IISs are comprehensive repositories of immunization information for children residing within a geographic region. The two models for participation in an IIS are voluntary inclusion, or "opt-in," and voluntary exclusion, or "opt-out." In an opt-in system, consent must be obtained for each participant, conversely, in an opt-out IIS, all children are included unless procedures to exclude the child are completed. Consent requirements for participation vary by state; the Texas IIS, ImmTrac, is an opt-in system.^ Objectives. The specific objectives are to: (1) Evaluate the variance among the time and costs associated with collecting ImmTrac consent at public and private birthing hospitals in the Greater Houston area; (2) Estimate the total costs associated with collecting ImmTrac consent at selected public and private birthing hospitals in the Greater Houston area; (3) Describe the alternative opt-out process for collecting ImmTrac consent at birth and discuss the associated cost savings relative to an opt-in system.^ Methods. Existing time-motion studies (n=281) conducted between October, 2006 and August, 2007 at 8 birthing hospitals in the Greater Houston area were used to assess the time and costs associated with obtaining ImmTrac consent at birth. All data analyzed are deidentified and contain no personal information. Variations in time and costs at each location were assessed and total costs per child and costs per year were estimated. The cost of an alternative opt-out system was also calculated.^ Results. The median time required by birth registrars to complete consent procedures varied from 72-285 seconds per child. The annual costs associated with obtaining consent for 388,285 newborns in ImmTrac's opt-in consent process were estimated at $702,000. The corresponding costs of the proposed opt-out system were estimated to total $194,000 per year. ^ Conclusions. Substantial variation in the time and costs associated with completion of ImmTrac consent procedures were observed. Changing to an opt-out system for participation could represent significant cost savings. ^

AN ANALYSIS OF THE RELATIVE INFLUENCE OF RACE, INCOME, EDUCATION, AND FOOD STAMP PROGRAM PARTICIPATION/NONPARTICIPATION ON THE FOOD AND NUTRIENT CONSUMPTION OF A NORTH FLORIDA URBAN CLINIC POPULATION IN CONJUNCTION WITH A SURVEY OF NUTRITION RELATED HABITS AND ATTITUDES

The relative influence of race, income, education, and Food Stamp Program participation/nonparticipation on the food and nutrient intake of 102 fecund women ages 18-45 years in a Florida urban clinic population was assessed using the technique of multiple regression analysis. Study subgroups were defined by race and Food Stamp Program participation status. Education was found to have the greatest influence on food and nutrient intake. Race was the next most influential factor followed in order by Food Stamp Program participation and income. The combined effect of the four independent variables explained no more than 19 percent of the variance for any of the food and nutrient intake variables. This would indicate that a more complex model of influences is needed if variations in food and nutrient intake are to be fully explained.^ A socioeconomic questionnaire was administered to investigate other factors of influence. The influence of the mother, frequency and type of restaurant dining, and perceptions of food intake and weight were found to be factors deserving further study.^ Dietary data were collected using the 24-hour recall and food frequency checklist. Descriptive dietary findings indicated that iron and calcium were nutrients where adequacy was of concern for all study subgroups. White Food Stamp Program participants had the greatest number of mean nutrient intake values falling below the 1980 Recommended Dietary Allowances (RDAs). When Food Stamp Program participants were contrasted to nonparticipants, mean intakes of six nutrients (kilocalories, calcium, iron, vitamin A, thiamin, and riboflavin) were below the 1980 RDA compared to five mean nutrient intakes (kilocalories, calcium, iron, thiamin and riboflavin) for the nonparticipants. Use of the Index of Nutritional Quality (INQ), however, revealed that the quality of the diet of Food Stamp Program participants per 1000 kilocalories was adequate with exception of calcium and iron. Intakes of these nutrients were also not adequate on a 1000 kilocalorie basis for the nonparticipant group. When mean nutrient intakes of the groups were compared using Student's t-test oleicacid intake was the only significant difference found. Being a nonparticipant in the Food Stamp Program was found to be associated with more frequent consumption of cookies, sweet rolls, doughnuts, and honey. The findings of this study contradict the negative image of the Food Stamp Program participant and emphasize the importance of education. ^

SOCIAL AND BIOLOGICAL DETERMINANTS OF SHORT-TERM GROWTH VELOCITY AMONG PRESCHOOLERS OF RURAL GUATEMALA: A PATH ANALYSIS APPROACH (WEIGHT-GAIN, IRON DEFICIENCY, GASTROINTESTINAL SYMPTOMS)

This dissertation develops and tests through path analysis a theoretical model to explain how socioeconomic, socioenvironmental, and biologic risk factors simultaneously influence each other to further produce short-term, depressed growth in preschoolers. Three areas of risk factors were identified: child's proximal environment, maturational stage, and biological vulnerability. The theoretical model represented both the conceptual framework and the nature and direction of the hypotheses. Original research completed in 1978-80 and in 1982 provided the background data. It was analyzed first by nested-analysis of variance, followed by path analysis. The study provided evidence of mild iron deficiency and gastrointestinal symptomatology in the etiology of depressed, short-term weight gain. Also, there was evidence suggesting that family resources for material and social survival significantly contribute to the variability of short-term, age-adjusted growth velocity. These results challenge current views of unifocal intervention, whether for prevention or control. For policy formulations, though, the mechanisms underlying any set of interlaced relationships must be decoded. Theoretical formulations here proposed should be reassessed under a more extensive research design. It is suggested that studies should be undertaken where social changes are actually in progress; otherwise, nutritional epidemiology in developing countries operates somewhere between social reality and research concepts, with little grasp of its real potential. The study stresses that there is a connection between substantive theory, empirical observation, and policy issues. ^

Analysis of interval -censored events in hypertension studies: Evaluation of treatment of coronary heart disease

Many statistical studies feature data with both exact-time and interval-censored events. While a number of methods currently exist to handle interval-censored events and multivariate exact-time events separately, few techniques exist to deal with their combination. This thesis develops a theoretical framework for analyzing a multivariate endpoint comprised of a single interval-censored event plus an arbitrary number of exact-time events. The approach fuses the exact-time events, modeled using the marginal method of Wei, Lin, and Weissfeld, with a piecewise-exponential interval-censored component. The resulting model incorporates more of the information in the data and also removes some of the biases associated with the exclusion of interval-censored events. A simulation study demonstrates that our approach produces reliable estimates for the model parameters and their variance-covariance matrix. As a real-world data example, we apply this technique to the Systolic Hypertension in the Elderly Program (SHEP) clinical trial, which features three correlated events: clinical non-fatal myocardial infarction, fatal myocardial infarction (two exact-time events), and silent myocardial infarction (one interval-censored event). ^

Q method factor analysis of stakeholder social perspectives of the effectiveness of Environmental Impact Assessment public participation in the Western Cape, South Africa

Public participation is an integral part of Environmental Impact Assessment (EIA), and as such, has been incorporated into regulatory norms. Assessment of the effectiveness of public participation has remained elusive however. This is partly due to the difficulty in identifying appropriate effectiveness criteria. This research uses Q methodology to discover and analyze stakeholder's social perspectives of the effectiveness of EIAs in the Western Cape, South Africa. It considers two case studies (Main Road and Saldanha Bay EIAs) for contextual participant perspectives of the effectiveness based on their experience. It further considers the more general opinion of provincial consent regulator staff at the Department of Environmental Affairs and the Department of Planning (DEA&DP). Two main themes of investigation are drawn from the South African National Environmental Management Act imperative for effectiveness: firstly, the participation procedure, and secondly, the stakeholder capabilities necessary for effective participation. Four theoretical frameworks drawn from planning, politics and EIA theory are adapted to public participation and used to triangulate the analysis and discussion of the revealed social perspectives. They consider citizen power in deliberation, Habermas' preconditions for the Ideal Speech Situation (ISS), a Foucauldian perspective of knowledge, power and politics, and a Capabilities Approach to public participation effectiveness. The empirical evidence from this research shows that the capacity and contextual constraints faced by participants demand the legislative imperatives for effective participation set out in the NEMA. The implementation of effective public participation has been shown to be a complex, dynamic and sometimes nebulous practice. The functional level of participant understanding of the process was found to be significantly wide-ranging with consequences of unequal and dissatisfied stakeholder engagements. Furthermore, the considerable variance of stakeholder capabilities in the South African social context, resulted in inequalities in deliberation. The social perspectives revealed significant differences in participant experience in terms of citizen power in deliberation. The ISS preconditions are highly contested in both the Saldanha EIA case study and the DEA&DP social perspectives. Only one Main Road EIA case study social perspective considered Foucault's notion of governmentality as a reality in EIA public participation. The freedom of control of ones environment, based on a Capabilities approach, is a highly contested notion. Although agreed with in principle, all of the social perspectives indicate that contextual and capacity realities constrain its realisation. This research has shown that Q method can be applied to EIA public participation in South Africa and, with the appropriate research or monitoring applications it could serve as a useful feedback tool to inform best practice public participation.