Case Studies in Bayesian Statistical Modelling and Analysis

Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: •Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. •Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. •Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.

Notes on the future of critical discourse studies

In How to Do Things with Words, Austin (1975) described marriages, sentencings and ship launchings as prototypes of performative utterance. What’s the appropriate speech act for launching an academic journal? First editions of journals tend to take a field as formed a priori, as having “come of age”, and state good intents to capture its best or most innovative work.

Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies

Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

Memory strength effects in fMRI studies: A matter of confidence

To investigate potentially dissociable recognition memory responses in the hippocampus and perirhinal cortex, fMRI studies have often used confidence ratings as an index of memory strength. Confidence ratings, although correlated with memory strength, also reflect sources of variability, including task-irrelevant item effects and differences both within and across individuals in terms of applying decision criteria to separate weak from strong memories. We presented words one, two, or four times at study in each of two different conditions, focused and divided attention, and then conducted separate fMRI analyses of correct old responses on the basis of subjective confidence ratings or estimates from single- versus dual-process recognition memory models. Overall, the effect of focussing attention on spaced repetitions at study manifested as enhanced recognition memory performance. Confidence- versus model-based analyses revealed disparate patterns of hippocampal and perirhinal cortex activity at both study and test and both within and across hemispheres. The failure to observe equivalent patterns of activity indicates that fMRI signals associated with subjective confidence ratings reflect additional sources of variability. The results are consistent with predictions of single-process models of recognition memory.

Genetic clustering on the hippocampal surface for genome-wide association studies

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

Modeling of the hemodynamic responses in block design fMRI studies

The hemodynamic response function (HRF) describes the local response of brain vasculature to functional activation. Accurate HRF modeling enables the investigation of cerebral blood flow regulation and improves our ability to interpret fMRI results. Block designs have been used extensively as fMRI paradigms because detection power is maximized; however, block designs are not optimal for HRF parameter estimation. Here we assessed the utility of block design fMRI data for HRF modeling. The trueness (relative deviation), precision (relative uncertainty), and identifiability (goodness-of-fit) of different HRF models were examined and test-retest reproducibility of HRF parameter estimates was assessed using computer simulations and fMRI data from 82 healthy young adult twins acquired on two occasions 3 to 4 months apart. The effects of systematically varying attributes of the block design paradigm were also examined. In our comparison of five HRF models, the model comprising the sum of two gamma functions with six free parameters had greatest parameter accuracy and identifiability. Hemodynamic response function height and time to peak were highly reproducible between studies and width was moderately reproducible but the reproducibility of onset time was low. This study established the feasibility and test-retest reliability of estimating HRF parameters using data from block design fMRI studies.

A stress and coping approach to organisational change: Evidence from three field studies

In this paper, a stress and coping perspective is used to outline the processes that determine employee adaptation to organisational change. A theoretical framework that simultaneously considers the effects of event characteristics, situational appraisals, coping strategies, and coping resources is reviewed. Three empirical investigations of organisational change that have tested various components of the model are then presented. In the first study, there was evidence linking event characteristics, situational appraisals, coping strategies and coping resources to levels of employee adjustment in a sample of pilots employed in a newly merged airline company. In a more focused test of the model with a sample of employees experiencing a restructuring process in their organisation it was found that the provision of change-related information enhanced levels of efficacy to deal with the change process which, in turn, predicted psychological wellbeing, client engagement, and job satisfaction. In a study of managers affected by a new remuneration scheme, there was evidence to suggest that managers who received change-specific information and opportunities to participate in the change process reported higher levels of change readiness. Managers who reported higher levels of readiness for change also reported higher levels of psychological wellbeing and job satisfaction. These studies highlight ways in which managers and change agents can help employees to cope during times of organisational change.

Experimental studies of lipped channel beams subject to web crippling under ETF and ITF load cases

Lipped channel beams (LCBs) are commonly used as floor joists and bearers in buildings. However, they are subjected to specific failure modes such as web crippling. Despite considerable web crippling research, recent studies [1-6] have shown that the current web crippling design rules are unable to predict the test capacities under ETF and ITF load cases. In many instances, the predictions by the available design standards such as AISI S100, AS/NZS 4600 and Eurocode 3 Part 1-3 [7-9] are inconsistent. Hence thirty-six tests were conducted to assess the web crippling behaviour and strengths of LCBs under two flange load cases. Experimental web crippling capacities were then compared with the predictions from the current design rules. These comparisons showed that AS/NZS 4600 and AISI S100 design equations are very unconservative for LCB sections under ETF load case and are conservative for ITF load case. Hence improved equations were proposed to determine the web crippling capacities of LCBs. Suitable design rules were also developed using the direct strength method. This paper presents the details of this study and the results including improved design rules.

Charge transport studies in donor-acceptor block copolymer PDPP-TNT and PC71BM based inverted organic photovoltaic devices processed in room conditions

Diketopyrrolopyrole-naphthalene polymer (PDPP-TNT), a donor-acceptor co-polymer, has shown versatile behavior demonstrating high performances in organic field-effect transistors (OFETs) and organic photovoltaic (OPV) devices. In this paper we report investigation of charge carrier dynamics in PDPP-TNT, and [6,6]-phenyl C71 butyric acid methyl ester (PC71BM) bulk-heterojunction based inverted OPV devices using current density-voltage (J-V) characteristics, space charge limited current (SCLC) measurements, capacitance-voltage (C-V) characteristics, and impedance spectroscopy (IS). OPV devices in inverted architecture, ITO/ZnO/PDPP-TNT:PC71BM/MoO3/Ag, are processed and characterized at room conditions. The power conversion efficiency (PCE) of these devices are measured ∼3.8%, with reasonably good fill-factor 54.6%. The analysis of impedance spectra exhibits electron’s mobility ∼2 × 10−3 cm2V−1s−1, and lifetime in the range of 0.03-0.23 ms. SCLC measurements give hole mobility of 1.12 × 10−5 cm2V−1s−1, and electron mobility of 8.7 × 10−4 cm2V−1s−1.

Correction: Genome-wide association studies of asthma in population-based cohorts confirm known and suggested loci and identify an additional association near HLA

Read the original article via 'related work' link below

Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA

Rationale: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives: To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods: The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x10-8) and three variants reported as suggestive (P<5×10-7). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results: We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×10-9). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (PStage1+Stage2 = 1.1x10-9), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (PStage1+Stage2 = 1.1x10-8), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions: Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma. © 2012 Ramasamy et al.

Finnish HLA studies confirm the increased risk conferred by HLA-B27 homozygosity in ankylosing spondylitis

Objective: To determine the influence of HLA-B27 homozygosity and HLA-DRB1 alleles in the susceptibility to, and severity of, ankylosing spondylitis in a Finnish population. Methods: 673 individuals from 261 families with ankylosing spondylitis were genotyped for HLA-DRB1 alleles and HLA-B27 heterozygosity/ homozygosity. The frequencies of HLA-B27 homozygotes in probands from these families were compared with the expected number of HLA-B27 homozygotes in controls under Hardy-Weinberg equilibrium (HWE). The effect of HLA-DRB1 alleles was assessed using a logistic regression procedure conditioned on HLA-B27 and case-control analysis. Results: HLA-B27 was detected in 93% of cases of ankylosing spondylitis. An overrepresentation of HLA-B27 homozygotes was noted in ankylosing spondylitis (11%) compared with the expected number of HLA-B27 homozygotes under HWE (4%) (odds ratio (OR) = 3.3 (95% confidence interval, 1.6 to 6.8), p = 0.002). HLA-B27 homozygosity was marginally associated with reduced BASDAI (HLA-B27 homozygotes, 4.5 (1.6); HLA-B27 heterozygotes, 5.4 (1.8) (mean (SD)), p = 0.05). Acute anterior uveitis (AAU) was present in significantly more HLA-B27 positive cases (50%) than HLA-B27 negative cases (16%) (OR = 5.4 (1.7 to 17), p<0.004). HLA-B27 positive cases had a lower average age of symptom onset (26.7 (8.0) years) compared with HLA-B27 negative cases (35.7 (11.2) years) (p<0.0001). Conclusions: HLA-627 homozygosity is associated with a moderately increased risk of ankylosing spondylitis compared with HLA-β27 heterozygosity. HLA-B27 positive cases had an earlier age of onset of ankylosing spondylitis than HLA-B27 negative cases and were more likely to develop AAU. HLA-DRB1 alleles may influence the age of symptom onset of ankylosing spondylitis.

Progress in spondylarthritis. Progress in studies of the genetics of ankylosing spondylitis

The advent of high-throughput SNP genotyping methods has advanced research into the genetics of common complex genetic diseases such as ankylosing spondylitis (AS) rapidly in recent times. The identification of associations with the genes IL23R and ERAP1 have been robustly replicated, and advances have been made in studies of the major histocompatibility complex genetics of AS, and of KIR gene variants and the disease. The findings are already being translated into increased understanding of the immunological pathways involved in AS, and raising novel potential therapies. The current studies in AS remain underpowered, and no full genomewide association study has yet been reported in AS; such studies are likely to add to the significant advances that have already been made.