The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has ...grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems.
The study of pigmentation has played an important role in the intersection of evolution, genetics, and developmental biology. Pigmentation's utility as a visible phenotypic marker has resulted in ...over 100 years of intense study of coat color mutations in laboratory mice, thereby creating an impressive list of candidate genes and an understanding of the developmental mechanisms responsible for the phenotypic effects. Variation in color and pigment patterning has also served as the focus of many classic studies of naturally occurring phenotypic variation in a wide variety of vertebrates, providing some of the most compelling cases for parallel and convergent evolution. Thus, the pigmentation model system holds much promise for understanding the nature of adaptation by linking genetic changes to variation in fitness-related traits. Here, I first discuss the historical role of pigmentation in genetics, development and evolutionary biology. I then discuss recent empirically based studies in vertebrates, which rely on these historical foundations to make connections between genotype and phenotype for ecologically important pigmentation traits. These studies provide insight into the evolutionary process by uncovering the genetic basis of adaptive traits and addressing such long-standing questions in evolutionary biology as (1) are adaptive changes predominantly caused by mutations in regulatory regions or coding regions? (2) is adaptation driven by the fixation of dominant mutations? and (3) to what extent are parallel phenotypic changes caused by similar genetic changes? It is clear that coloration has much to teach us about the molecular basis of organismal diversity, adaptation and the evolutionary process.
Statistical network models describing multivariate dependency structures in psychological data have gained increasing popularity. Such comparably novel statistical techniques require specific ...guidelines to make them accessible to the research community. So far, researchers have provided tutorials guiding the estimation of networks and their accuracy. However, there is currently little guidance in determining what parts of the analyses and results should be documented in a scientific report. A lack of such reporting standards may foster researcher degrees of freedom and could provide fertile ground for questionable reporting practices. Here, we introduce reporting standards for network analyses in cross-sectional data, along with a tutorial and two examples. The presented guidelines are aimed at researchers as well as the broader scientific community, such as reviewers and journal editors evaluating scientific work. We conclude by discussing how the network literature specifically can benefit from such guidelines for reporting and transparency.
Translational Abstract
In recent years, network models have become increasingly popular in the field of psychology. Such comparably novel statistical techniques require specific guidelines to make them accessible to the research community. So far, researchers have provided tutorials guiding how network analysis can be applied to psychological data. However, there is currently little guidance in determining what parts of the analyses and results should be documented in a scientific report. A lack of such reporting standards may result in researchers being confronted with too much choice in reporting their results, which in turn might provide fertile ground for questionable reporting practices. Here, we introduce reporting standards for network analyses in cross-sectional data, along with a tutorial and two examples. The presented guidelines are aimed at researchers as well as the broader scientific community, such as reviewers and journal editors evaluating scientific work. We conclude by discussing how the network literature specifically can benefit from such guidelines for reporting and transparency.
Abstract
We describe and test the pipeline used to measure the weak-lensing shear signal from the Kilo-Degree Survey (KiDS). It includes a novel method of ‘self-calibration’ that partially corrects ...for the effect of noise bias. We also discuss the ‘weight bias’ that may arise in optimally weighted measurements, and present a scheme to mitigate that bias. To study the residual biases arising from both galaxy selection and shear measurement, and to derive an empirical correction to reduce the shear biases to ≲1 per cent, we create a suite of simulated images whose properties are close to those of the KiDS survey observations. We find that the use of ‘self-calibration’ reduces the additive and multiplicative shear biases significantly, although further correction via a calibration scheme is required, which also corrects for a dependence of the bias on galaxy properties. We find that the calibration relation itself is biased by the use of noisy, measured galaxy properties, which may limit the final accuracy that can be achieved. We assess the accuracy of the calibration in the tomographic bins used for the KiDS cosmic shear analysis, testing in particular the effect of possible variations in the uncertain distributions of galaxy size, magnitude and ellipticity, and conclude that the calibration procedure is accurate at the level of multiplicative bias ≲1 per cent required for the KiDS cosmic shear analysis.
We present measurements of the masses of 20 X-ray luminous clusters of galaxies at intermediate redshifts, determined from a weak-lensing analysis of deep archival R-band data obtained using the ...Canada–France–Hawaii Telescope. Compared to previous work, our analysis accounts for a number of effects that are typically ignored, but can lead to small biases, or incorrect error estimates. We derive masses that are essentially model-independent and find that they agree well with measurements of the velocity dispersion of cluster galaxies and with the results of X-ray studies. Assuming a power law between the lensing mass and the X-ray temperature, M2500∝Tα, we find a best-fitting slope of α= 1.34+0.30−0.28. This slope agrees with self-similar cluster models and studies based on X-ray data alone. For a cluster with a temperature of kT= 5 keV we obtain a mass M2500= (1.4 ± 0.2) × 1014 h−1 M⊙ in fair agreement with recent Chandra and XMM studies.
Abstract
We present measurements of the weak gravitational lensing shear power spectrum based on
$450 \deg ^2$
of imaging data from the Kilo Degree Survey. We employ a quadratic estimator in two and ...three redshift bins and extract band powers of redshift autocorrelation and cross-correlation spectra in the multipole range 76 ≤ ℓ ≤ 1310. The cosmological interpretation of the measured shear power spectra is performed in a Bayesian framework assuming a ΛCDM model with spatially flat geometry, while accounting for small residual uncertainties in the shear calibration and redshift distributions as well as marginalizing over intrinsic alignments, baryon feedback and an excess-noise power model. Moreover, massive neutrinos are included in the modelling. The cosmological main result is expressed in terms of the parameter combination
$S_8 \equiv \sigma _8 \sqrt{\Omega _{\rm m}/0.3}$
yielding S
8 = 0.651 ± 0.058 (three z-bins), confirming the recently reported tension in this parameter with constraints from Planck at 3.2σ (three z-bins). We cross-check the results of the three z-bin analysis with the weaker constraints from the two z-bin analysis and find them to be consistent. The high-level data products of this analysis, such as the band power measurements, covariance matrices, redshift distributions and likelihood evaluation chains are available at http://kids.strw.leidenuniv.nl.
We present cosmological parameter constraints from a tomographic weak gravitational lensing analysis of ~450 deg super( 2) of imaging data from the Kilo Degree Survey (KiDS). For a flat ... cold dark ...matter (...CDM) cosmology with a prior on H sub( 0) that encompasses the most recent direct measurements, we find S sub( 8) ... = 0.745 plus or minus 0.039. This result is in good agreement with other low-redshift probes of large-scale structure, including recent cosmic shear results, along with pre-Planck cosmic microwave background constraints. A 2.3... tension in S sub( 8) and 'substantial discordance' in the full parameter space is found with respect to the Planck 2015 results. We use shear measurements for nearly 15 million galaxies, determined with a new improved 'self-calibrating' version of lensfit validated using an extensive suite of image simulations. Four-band ugri photometric redshifts are calibrated directly with deep spectroscopic surveys. The redshift calibration is confirmed using two independent techniques based on angular cross-correlations and the properties of the photometric redshift probability distributions. Our covariance matrix is determined using an analytical approach, verified numerically with large mock galaxy catalogues. We account for uncertainties in the modelling of intrinsic galaxy alignments and the impact of baryon feedback on the shape of the non-linear matter power spectrum, in addition to the small residual uncertainties in the shear and redshift calibration. The cosmology analysis was performed blind. Our high-level data products, including shear correlation functions, covariance matrices, redshift distributions, and Monte Carlo Markov chains are available at http://kids.strw.leidenuniv.nl. (ProQuest: ... denotes formulae/symbols omitted.)
A central challenge in evolutionary biology is to identify genes underlying ecologically important traits and describe the fitness consequences of naturally occurring variation at these loci. To ...address this goal, several novel approaches have been developed, including 'population genomics,' where a large number of molecular markers are scored in individuals from different environments with the goal of identifying markers showing unusual patterns of variation, potentially due to selection at linked sites. Such approaches are appealing because of (1) the increasing ease of generating large numbers of genetic markers, (2) the ability to scan the genome without measuring phenotypes and (3) the simplicity of sampling individuals without knowledge of their breeding history. Although such approaches are inherently applicable to non-model systems, to date these studies have been limited in their ability to uncover functionally relevant genes. By contrast, quantitative genetics has a rich history, and more recently, quantitative trait locus (QTL) mapping has had some success in identifying genes underlying ecologically relevant variation even in novel systems. QTL mapping, however, requires (1) genetic markers that specifically differentiate parental forms, (2) a focus on a particular measurable phenotype and (3) controlled breeding and maintenance of large numbers of progeny. Here we present current advances and suggest future directions that take advantage of population genomics and quantitative genetic approaches - in both model and non-model systems. Specifically, we discuss advantages and limitations of each method and argue that a combination of the two provides a powerful approach to uncovering the molecular mechanisms responsible for adaptation.
We present a combined tomographic weak gravitational lensing analysis of the Kilo Degree Survey (KV450) and the Dark Energy Survey (DES-Y1). We homogenize the analysis of these two public cosmic ...shear datasets by adopting consistent priors and modeling of nonlinear scales, and determine new redshift distributions for DES-Y1 based on deep public spectroscopic surveys. Adopting these revised redshifts results in a 0.8 σ reduction in the DES-inferred value for S 8 , which decreases to a 0.5 σ reduction when including a systematic redshift calibration error model from mock DES data based on the MICE2 simulation. The combined KV450+DES-Y1 constraint on S 8 = 0.762 −0.024 +0.025 is in tension with the Planck 2018 constraint from the cosmic microwave background at the level of 2.5 σ . This result highlights the importance of developing methods to provide accurate redshift calibration for current and future weak-lensing surveys.
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