Combining Information from Multiple Sources in Bayesian Modeling

Surveys can collect important data that inform policy decisions and drive social science research. Large government surveys collect information from the U.S. population on a wide range of topics, including demographics, education, employment, and lifestyle. Analysis of survey data presents unique challenges. In particular, one needs to account for missing data, for complex sampling designs, and for measurement error. Conceptually, a survey organization could spend lots of resources getting high-quality responses from a simple random sample, resulting in survey data that are easy to analyze. However, this scenario often is not realistic. To address these practical issues, survey organizations can leverage the information available from other sources of data. For example, in longitudinal studies that suffer from attrition, they can use the information from refreshment samples to correct for potential attrition bias. They can use information from known marginal distributions or survey design to improve inferences. They can use information from gold standard sources to correct for measurement error.

This thesis presents novel approaches to combining information from multiple sources that address the three problems described above.

The first method addresses nonignorable unit nonresponse and attrition in a panel survey with a refreshment sample. Panel surveys typically suffer from attrition, which can lead to biased inference when basing analysis only on cases that complete all waves of the panel. Unfortunately, the panel data alone cannot inform the extent of the bias due to attrition, so analysts must make strong and untestable assumptions about the missing data mechanism. Many panel studies also include refreshment samples, which are data collected from a random sample of new

individuals during some later wave of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by nonignorable attrition while reducing reliance on strong assumptions about the attrition process. To date, these bias correction methods have not dealt with two key practical issues in panel studies: unit nonresponse in the initial wave of the panel and in the

refreshment sample itself. As we illustrate, nonignorable unit nonresponse

can significantly compromise the analyst's ability to use the refreshment samples for attrition bias correction. Thus, it is crucial for analysts to assess how sensitive their inferences---corrected for panel attrition---are to different assumptions about the nature of the unit nonresponse. We present an approach that facilitates such sensitivity analyses, both for suspected nonignorable unit nonresponse

in the initial wave and in the refreshment sample. We illustrate the approach using simulation studies and an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

The second method incorporates informative prior beliefs about

marginal probabilities into Bayesian latent class models for categorical data.

The basic idea is to append synthetic observations to the original data such that

(i) the empirical distributions of the desired margins match those of the prior beliefs, and (ii) the values of the remaining variables are left missing. The degree of prior uncertainty is controlled by the number of augmented records. Posterior inferences can be obtained via typical MCMC algorithms for latent class models, tailored to deal efficiently with the missing values in the concatenated data.

We illustrate the approach using a variety of simulations based on data from the American Community Survey, including an example of how augmented records can be used to fit latent class models to data from stratified samples.

The third method leverages the information from a gold standard survey to model reporting error. Survey data are subject to reporting error when respondents misunderstand the question or accidentally select the wrong response. Sometimes survey respondents knowingly select the wrong response, for example, by reporting a higher level of education than they actually have attained. We present an approach that allows an analyst to model reporting error by incorporating information from a gold standard survey. The analyst can specify various reporting error models and assess how sensitive their conclusions are to different assumptions about the reporting error process. We illustrate the approach using simulations based on data from the 1993 National Survey of College Graduates. We use the method to impute error-corrected educational attainments in the 2010 American Community Survey using the 2010 National Survey of College Graduates as the gold standard survey.

Bayesian Methods for Inferring Gene Regulatory Networks

Thesis (Ph.D.)--University of Washington, 2016-08

Developmental vitamin D deficiency alters adult behaviour: An informative animal model of schizophrenia

Background: There is growing evidence that vitamin D is active in the brain but until recently there was a lack of evidence about its role during brain development. Guided by certain features of the epidemiology of schizophrenia, we have explored the role of vitamin D in the developing brain and behaviour using whole animal models. Methods: Sprague-Dawley rats were fed a vitamin D deficient diet (DVD) or control diet 6 weeks prior to mating and housed under UVB-free lighting conditions. On the day of birth all rats were fed a control diet for the remainder of the study. We observed behaviour at two timepoints; on the day of birth to study maternal behaviour, and at 10 weeks of age to study offspring behaviour in adulthood, under baseline and drug induced conditions (MK-801, haloperidol, amphetamine). Results: Prenatal vitamin D deficiency results in subtle alterations in maternal behaviour as well as long lasting effects on the adult offspring, despite a return to normal vitamin D levels during postnatal life. These affects were specific to transient prenatal vitamin D depletion as adult vitamin D depletion, combined prenatal and chronic postnatal vitamin D depletion, or ablation of the vitamin D receptor in mice led to markedly different outcomes. Conclusions: The developmental vitamin D (DVD) model now draws strength from epidemiological evidence of schizophrenia and animal experiments. Although the DVD model does not replicate every aspect of schizophrenia, it has several attractive features: (1) the exposure is based on clues from epidemiology; (2) it reproduces the increase in lateral ventricles; (3) it reproduces well-regarded behavioural phenotypes associated with schizophrenia (e.g. MK- 801 induced hyperlocomotion); and (4) it implicates a disturbance in dopamine signaling. In summary, low prenatal levels of vitamin D can influence critical components of orderly brain development and that this has a long lasting effect on behaviour.

Security prices and market transparency: the role of prior information

This paper analyzes the role of traders' priors (proper versus improper) on the implications of market transparency by comparing a pre-trade transparent market with an opaque market in a set-up based on Madhavan (1996). We show that prices may be more informative in the opaque market, regardless of how priors are modelled. In contrast, the comparison of market liquidity and volatility in the two market structures are affected by prior specification. Key words: Market microstructure, Transparency, Prior information

A comparison of reverse osmosis, nanofiltration and ultrafiltration as concentration processes for skim milk prior to drying

Skim milk was concentrated by reverse osmosis (RO), nanofiltration (NF) and ultrafiltration (UF) and the retentates were spray-dried. The resulting powders were reconstituted to 25% TS and sterilised to evaluate their heat stability. Reverse osmosis led to maximum retention of calcium, a fall in pH for its retentate and its reconstituted powder. All RO powders produced a weak gel on heating. Some calcium was lost during NF and a greater amount during UF. Their resulting reconstituted powders had a higher pH than those produced by RO. Powders produced by UF showed poor heat stability. Only one powder produced by NF showed good heat stability. This could be improved by addition of stabilisers at appropriate addition rates.

A Note on the Prior Distributions of Weibull Parameters for the Reliability Function

In Bayesian Inference it is often desirable to have a posterior density reflecting mainly the information from sample data. To achieve this purpose it is important to employ prior densities which add little information to the sample. We have in the literature many such prior densities, for example, Jeffreys (1967), Lindley (1956); (1961), Hartigan (1964), Bernardo (1979), Zellner (1984), Tibshirani (1989), etc. In the present article, we compare the posterior densities of the reliability function by using Jeffreys, the maximal data information (Zellner, 1984), Tibshirani's, and reference priors for the reliability function R(t) in a Weibull distribution.

Bayesian analysis of weak gravitational lensing and Sunyaev-Zel'dovich data for six galaxy clusters

We present an analysis of observations made with the Arcminute Microkelvin Imager (AMI) and the CanadaFranceHawaii Telescope (CFHT) of six galaxy clusters in a redshift range of 0.160.41. The cluster gas is modelled using the SunyaevZeldovich (SZ) data provided by AMI, while the total mass is modelled using the lensing data from the CFHT. In this paper, we (i) find very good agreement between SZ measurements (assuming large-scale virialization and a gas-fraction prior) and lensing measurements of the total cluster masses out to r200; (ii) perform the first multiple-component weak-lensing analysis of A115; (iii) confirm the unusual separation between the gas and mass components in A1914 and (iv) jointly analyse the SZ and lensing data for the relaxed cluster A611, confirming our use of a simulation-derived masstemperature relation for parametrizing measurements of the SZ effect.

Targeted development of informative microsatellite (SSR) markers

We describe a novel approach, selectively amplified microsatellite (SAM) analysis, for the targeted development of informative simple sequence repeat (SSR) markers. A modified selectively amplified microsatellite polymorphic loci assay is used to generate multi-locus SSR fingerprints that provide a source of polymorphic DNA markers (SAMs) for use in genetic studies. These polymorphisms capture the repeat length variation associated with SSRs and allow their chromosomal location to be determined prior to the expense of isolating and characterising individual loci. SAMs can then be converted to locus-specific SSR markers with the design and synthesis of a single primer specific to the conserved region flanking the repeat. This approach offers a cost-efficient and rapid method for developing SSR markers for predetermined chromosomal locations and of potential informativeness. The high recovery rate of useful SSR markers makes this strategy a valuable tool for population and genetic mapping studies. The utility of SAM analysis was demonstrated by the development of SSR markers in bread wheat.

Measurement Of Longitudinal Spin Asymmetries For Weak Boson Production In Polarized Proton-proton Collisions At Rhic.

We report measurements of single- and double-spin asymmetries for W^{±} and Z/γ^{*} boson production in longitudinally polarized p+p collisions at sqrt[s]=510  GeV by the STAR experiment at RHIC. The asymmetries for W^{±} were measured as a function of the decay lepton pseudorapidity, which provides a theoretically clean probe of the proton's polarized quark distributions at the scale of the W mass. The results are compared to theoretical predictions, constrained by polarized deep inelastic scattering measurements, and show a preference for a sizable, positive up antiquark polarization in the range 0.05

Interplay Of Weak Interactions In The Atom-by-atom Condensation Of Xenon Within Quantum Boxes.

Condensation processes are of key importance in nature and play a fundamental role in chemistry and physics. Owing to size effects at the nanoscale, it is conceptually desired to experimentally probe the dependence of condensate structure on the number of constituents one by one. Here we present an approach to study a condensation process atom-by-atom with the scanning tunnelling microscope, which provides a direct real-space access with atomic precision to the aggregates formed in atomically defined 'quantum boxes'. Our analysis reveals the subtle interplay of competing directional and nondirectional interactions in the emergence of structure and provides unprecedented input for the structural comparison with quantum mechanical models. This approach focuses on-but is not limited to-the model case of xenon condensation and goes significantly beyond the well-established statistical size analysis of clusters in atomic or molecular beams by mass spectrometry.

Modulation of post-coital dopaminergic tone by prior parity

The aim of this study was to investigate the possible effects of reproductive experience on dopaminergic profile in three different brain tissues, hypothalamus, striatum and cortex in rats on 7th-8th day of pregnancy during the light-dark shift (between 1700-1900h). Results showed that in hypothalamus, dopamine levels increased and DOPAC/DA decreased as a function of parity. In cortex, no differences were observed. In striata, the haloperidol-induced HVA and HVA/DA increases were less intense in experienced animals. These findings suggested that reproductive experience produced functional central changes during pregnancy, with different neurochemical responses depending on the brain region.

THE SLOAN NEARBY CLUSTER WEAK LENSING SURVEY

We describe and present initial results of a weak lensing survey of nearby (z less than or similar to 0.1) galaxy clusters in the Sloan Digital Sky Survey (SDSS). In this first study, galaxy clusters are selected from the SDSS spectroscopic galaxy cluster catalogs of Miller et al. and Berlind et al. We report a total of seven individual low-redshift cluster weak lensing measurements that include A2048, A1767, A2244, A1066, A2199, and two clusters specifically identified with the C4 algorithm. Our program of weak lensing of nearby galaxy clusters in the SDSS will eventually reach similar to 200 clusters, making it the largest weak lensing survey of individual galaxy clusters to date.

Kinetic energy sum spectra in nonmesonic weak decay of hypernuclei

We evaluate the coincidence spectra in the nonmesonic weak decay (NMWD) Lambda N -> nN of Lambda hypernuclei (4)(Lambda)He, (5)(Lambda)He, (12)(Lambda)C, (16)(Lambda)O, and (28)(Lambda)Si, as a function of the sum of kinetic energies E(nN)=E(n)+E(N) for N=n,p. The strangeness-changing transition potential is described by the one-meson-exchange model, with commonly used parametrization. Two versions of the independent-particle shell model (IPSM) are employed to account for the nuclear structure of the final residual nuclei. They are as follows: (a) IPSM-a, where no correlation, except for the Pauli principle, is taken into account and (b) IPSM-b, where the highly excited hole states are considered to be quasistationary and are described by Breit-Wigner distributions, whose widths are estimated from the experimental data. All np and nn spectra exhibit a series of peaks in the energy interval 110 MeV < E(nN)< 170 MeV, one for each occupied shell-model state. Within the IPSM-a, and because of the recoil effect, each peak covers an energy interval proportional to A(-1) , going from congruent to 4 MeV for (28)(Lambda)Si to congruent to 40 MeV for (4)(Lambda)He. Such a description could be pretty fair for the light (4)(Lambda)He and (5)(Lambda)He hypernuclei. For the remaining, heavier, hypernuclei it is very important, however, to consider as well the spreading in strength of the deep-hole states and bring into play the IPSM-b approach. Notwithstanding the nuclear model that is employed the results depend only very weakly on the details of the dynamics involved in the decay process proper. We propose that the IPSM is the appropriate lowest-order approximation for the theoretical calculations of the of kinetic energy sum spectra in the NMWD. It is in comparison to this picture that one should appraise the effects of the final-state interactions and of the two-nucleon-induced decay mode.

Effect of weak dipolar interaction on the magnetic properties of Ni nanoparticles assembly analyzed with different protocols

The effect of weak dipolar interactions (DIs) between Ni nanoparticles (NPs) in samples with different Ni concentrations was investigated by performing a detailed characterization of their structural and magnetic properties. From the determination of several physical parameters of Ni NP assemblies, it was found that the ac and dc magnetic susceptibility measurements are valuable for identifying the DIs between NPs while hysteresis loops measurements showed to be very insensitive, provided that the strength of the DI field is much smaller than the maximum coercive field. Therefore, the sensitivity of the observed static and dynamical magnetic properties to the effect of weak DI depends on the measurement protocols used. (C) 2011 American Institute of Physics. [doi:10.1063/1.3556767]

Weak measurement: Effect of the detector dynamics

The contribution of the detector dynamics to the weak measurement is analyzed. According to the usual theory [Y. Aharonov, D. Z. Albert, and L. Vaidman, Phys. Rev. Lett. 60, 1351 (1988)] the outcome of a weak measurement with preselection and postselection can be expressed as the real part of a complex number: the weak value. By accounting for the Hamiltonian evolution of the detector, here we find that there is a contribution proportional to the imaginary part of the weak value to the outcome of the weak measurement. This is due to the coherence of the probe being essential for the concept of complex weak value to be meaningful. As a particular example, we consider the measurement of a spin component and find that the contribution of the imaginary part of the weak value is sizable.