Estimating structural mean models with multiple instrumental variables using the generalised method of moments

Instrumental variables analysis using genetic markers as instruments is now a widely used technique in epidemiology and biostatistics. As single markers tend to explain only a small proportion of phenotypical variation, there is increasing interest in using multiple genetic markers to obtain more precise estimates of causal parameters. Structural mean models (SMMs) are semi-parametric models that use instrumental variables to identify causal parameters, but there has been little work on using these models with multiple instruments, particularly for multiplicative and logistic SMMs. In this paper, we show how additive, multiplicative and logistic SMMs with multiple discrete instrumental variables can be estimated efficiently using the generalised method of moments (GMM) estimator, how the Hansen J-test can be used to test for model mis-specification, and how standard GMM software routines can be used to fit SMMs. We further show that multiplicative SMMs, like the additive SMM, identify a weighted average of local causal effects if selection is monotonic. We use these methods to reanalyse a study of the relationship between adiposity and hypertension using SMMs with two genetic markers as instruments for adiposity. We find strong effects of adiposity on hypertension, but no evidence of unobserved confounding.

Estimating Structural Mean Models with Multiple Instrumental Variables using the Generalised Method of Moments

Instrumental variables analysis using genetic markers as instruments is now a widely used technique in epidemiology and biostatistics. As single markers tend to explain only a small proportion of phenotypical variation, there is increasing interest in using multiple genetic markers to obtain more precise estimates of causal parameters. Structural mean models (SMMs) are semi-parametric models that use instrumental variables to identify causal parameters, but there has been little work on using these models with multiple instruments, particularly for multiplicative and logistic SMMs. In this paper, we show how additive, multiplicative and logistic SMMs with multiple discrete instrumental variables can be estimated efficiently using the generalised method of moments (GMM) estimator, how the Hansen J-test can be used to test for model mis-specification, and how standard GMM software routines can be used to fit SMMs. We further show that multiplicative SMMs, like the additive SMM, identify a weighted average of local causal effects if selection is monotonic. We use these methods to reanalyse a study of the relationship between adiposity and hypertension using SMMs with two genetic markers as instruments for adiposity. We find strong effects of adiposity on hypertension, but no evidence of unobserved confounding.Structural Mean Models, Multiple Instrumental Variables, Generalised Method of Moments, Mendelian Randomisation, Local Average Treatment Effects

Estimating Structural Mean Models with Multiple Instrumental Variables Using the Generalised Method of Moments

Instrumental variables analysis using genetic markers as instruments is now a widely used technique in epidemiology and biostatistics. As single markers tend to explain only a small proportion of phenotypic variation, there is increasing interest in using multiple genetic markers to obtain more precise estimates of causal parameters. Structural mean models (SMMs) are semiparametric models that use instrumental variables to identify causal parameters. Recently, interest has started to focus on using these models with multiple instruments, particularly for multiplicative and logistic SMMs. In this paper we show how additive, multiplicative and logistic SMMs with multiple orthogonal binary instrumental variables can be estimated efficiently in models with no further (continuous) covariates, using the generalised method of moments (GMM) estimator. We discuss how the Hansen J-test can be used to test for model misspecification, and how standard GMM software routines can be used to fit SMMs. We further show that multiplicative SMMs, like the additive SMM, identify a weighted average of local causal effects if selection is monotonic. We use these methods to reanalyse a study of the relationship between adiposity and hypertension using SMMs with two genetic markers as instruments for adiposity. We find strong effects of adiposity on hypertension

Optimal Pricing in the Presence of Experience Effects

In this paper we analyze the problem of optimal intertemporal pricing for a monopolist when current (and past) output affect future cost and/or demand conditions through experience in production and/or in consumption. Learning by doing, the experience curve, contagion, habit formation, bandwagon, and snob effects are all examples of terminologies used to describe such situations. We call these experience effects for convenience and explore profit-maximizing pricing behavior when such effects exis

Creating citizen-consumers? Public service reform and (un)willing selves

About the book: Postmodern theories heralded the "death of the subject", and thereby deeply contested our intuition that we are free and willing selves. In recent times, the (free) will has come under attack yet again. Findings from the neuro- and cognitive sciences claim the concept of will to be scientifically untenable, specifying that it is our brain rather than our 'self' which decides what we want to do. In spite of these challenges however, the willing self has come to take centre stage in our society: juridical and moral practices ascribing guilt, or the organization of everyday life attributing responsibilities, for instance, can hardly be understood without taking recourse to the willing subject. In this vein, the authors address topics such as the genealogy of the concept of willing selves, the discourse on agency in neuroscience and sociology, the political debate on volition within neoliberal and neoconservative regimes, approaches toward novel forms of relational responsibility as well as moral evaluations in conceptualizing autonomy

Resource-Bound Quantification for Graph Transformation

Graph transformation has been used to model concurrent systems in software engineering, as well as in biochemistry and life sciences. The application of a transformation rule can be characterised algebraically as construction of a double-pushout (DPO) diagram in the category of graphs. We show how intuitionistic linear logic can be extended with resource-bound quantification, allowing for an implicit handling of the DPO conditions, and how resource logic can be used to reason about graph transformation systems

Source to Accretion Disk Tilt

Many different system types retrogradely precess, and retrograde precession could be from a tidal torque by the secondary on a misaligned accretion disk. However, a source to cause and maintain disk tilt is unknown. In this work, we show that accretion disks can tilt due to a force called lift. Lift results from differing gas stream supersonic speeds over and under an accretion disk. Because lift acts at the disk's center of pressure, a torque is applied around a rotation axis passing through the disk's center of mass. The disk responds to lift by pitching around the disk's line of nodes. If the gas stream flow ebbs, then lift also ebbs and the disk attempts to return to its original orientation. To first approximation, lift does not depend on magnetic fields or radiation sources but does depend on mass and the surface area of the disk. Also, for disk tilt to be initiated, a minimum mass transfer rate must be exceeded. For example, a $10^{-11}M_{\odot}$ disk around a 0.8$M_{\odot}$ compact central object requires a mass transfer rate greater than $\sim10^{-13}$M$_{\odot}$yr$^{-1}$, a value well below known mass transfer rates in Cataclysmic Variable Dwarf Novae systems that retrogradely precess and that exhibit negative superhumps in their light curves and a value well below mass transfer rates in protostellar forming systems

Uncomplicated obesity is associated with abnormal aortic function assessed by cardiovascular magnetic resonance

AIMS: Obese subjects with insulin resistance and hypertension have abnormal aortic elastic function, which may predispose them to the development of left ventricular dysfunction. We hypothesised that obesity, uncomplicated by other cardiovascular risk factors, is independently associated with aortic function. METHODS AND RESULTS: We used magnetic resonance imaging to measure aortic compliance, distensibility and stiffness index in 27 obese subjects (BMI 33 kg/m2) without insulin resistance and with normal cholesterol and blood pressure, and 12 controls (BMI 23 kg/m2). Obesity was associated with reduced aortic compliance (0.9 +/- 0.1 vs. 1.5 +/- 0.2 mm2/mmHg in controls, p < 0.02) and distensibility (3.3 +/- 0.01 vs. 5.6 +/- 0.01 mmHg-1 x 10-3, p < 0.02), as well as higher stiffness index (3.4 +/- 0.3 vs. 2.1 +/- 0.1, p < 0.02). Body mass index and fat mass were negatively correlated with aortic function. Leptin was higher in obesity (8.9 +/- 0.6 vs. 4.7 +/- 0.6 ng/ml, p < 0.001) and also correlated with aortic measures. In multiple regression models, fat mass, leptin and body mass index were independent predictors of aortic function. CONCLUSION: Aortic elastic function is abnormal in obese subjects without other cardiovascular risk factors. These findings highlight the independent importance of obesity in the development of cardiovascular disease

Embodied Discourses of Literacy in the Lives of Two Preservice Teachers

This study examines the emerging teacher literacy identities of Ian and A.J., two preservice teachers in a graduate teacher education program in the United States. Using a poststructural feminisms theoretical framework, the study illustrates the embodiment of literacy pedagogy discourses in relation to the literacy courses’ discourse of comprehensive literacy and the literacy biographical discourses of Ian and A.J. The results of this study indicate the need to deconstruct how the discourse of comprehensive literacy limits how we, as literacy teacher educators, position, hear and respond to our preservice teachers and suggests the need for differentiation in our teacher education literacy courses

Generation of Porous Particle Structures using the Void Expansion Method

The newly developed "void expansion method" allows for an efficient generation of porous packings of spherical particles over a wide range of volume fractions using the discrete element method. Particles are randomly placed under addition of much smaller "void-particles". Then, the void-particle radius is increased repeatedly, thereby rearranging the structural particles until formation of a dense particle packing. The structural particles' mean coordination number was used to characterize the evolving microstructures. At some void radius, a transition from an initially low to a higher mean coordination number is found, which was used to characterize the influence of the various simulation parameters. For structural and void-particle stiffnesses of the same order of magnitude, the transition is found at constant total volume fraction slightly below the random close packing limit. For decreasing void-particle stiffness the transition is shifted towards a smaller void-particle radius and becomes smoother.Comment: 9 pages, 8 figure