Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

Mixture Cure Survival Models with Dependent Censoring

A number of authors have studies the mixture survival model to analyze survival data with nonnegligible cure fractions. A key assumption made by these authors is the independence between the survival time and the censoring time. To our knowledge, no one has studies the mixture cure model in the presence of dependent censoring. To account for such dependence, we propose a more general cure model which allows for dependent censoring. In particular, we derive the cure models from the perspective of competing risks and model the dependence between the censoring time and the survival time using a class of Archimedean copula models. Within this framework, we consider the parameter estimation, the cure detection, and the two-sample comparison of latency distribution in the presence of dependent censoring when a proportion of patients is deemed cured. Large sample results using the martingale theory are obtained. We applied the proposed methodologies to the SEER prostate cancer data.

LIKELIHOOD ESTIMATION OF CONJUGACY RELATIONSHIPS IN LINEAR MODELS WITH APPLICATIONS TO HIGH-THROUGHPUT GENOMICS

In the simultaneous estimation of a large number of related quantities, multilevel models provide a formal mechanism for efficiently making use of the ensemble of information for deriving individual estimates. In this article we investigate the ability of the likelihood to identify the relationship between signal and noise in multilevel linear mixed models. Specifically, we consider the ability of the likelihood to diagnose conjugacy or independence between the signals and noises. Our work was motivated by the analysis of data from high-throughput experiments in genomics. The proposed model leads to a more flexible family. However, we further demonstrate that adequately capitalizing on the benefits of a well fitting fully-specified likelihood in the terms of gene ranking is difficult.

Steady-state function of the ubiquitous mammalian Na/H exchanger (NHE1) in relation to dimer coupling models with 2Na/2H stoichiometry

We describe the steady-state function of the ubiquitous mammalian Na/H exchanger (NHE)1 isoform in voltage-clamped Chinese hamster ovary cells, as well as other cells, using oscillating pH-sensitive microelectrodes to quantify proton fluxes via extracellular pH gradients. Giant excised patches could not be used as gigaseal formation disrupts NHE activity within the patch. We first analyzed forward transport at an extracellular pH of 8.2 with no cytoplasmic Na (i.e., nearly zero-trans). The extracellular Na concentration dependence is sigmoidal at a cytoplasmic pH of 6.8 with a Hill coefficient of 1.8. In contrast, at a cytoplasmic pH of 6.0, the Hill coefficient is <1, and Na dependence often appears biphasic. Results are similar for mouse skin fibroblasts and for an opossum kidney cell line that expresses the NHE3 isoform, whereas NHE1(-/-) skin fibroblasts generate no proton fluxes in equivalent experiments. As proton flux is decreased by increasing cytoplasmic pH, the half-maximal concentration (K(1/2)) of extracellular Na decreases less than expected for simple consecutive ion exchange models. The K(1/2) for cytoplasmic protons decreases with increasing extracellular Na, opposite to predictions of consecutive exchange models. For reverse transport, which is robust at a cytoplasmic pH of 7.6, the K(1/2) for extracellular protons decreases only a factor of 0.4 when maximal activity is decreased fivefold by reducing cytoplasmic Na. With 140 mM of extracellular Na and no cytoplasmic Na, the K(1/2) for cytoplasmic protons is 50 nM (pH 7.3; Hill coefficient, 1.5), and activity decreases only 25% with extracellular acidification from 8.5 to 7.2. Most data can be reconstructed with two very different coupled dimer models. In one model, monomers operate independently at low cytoplasmic pH but couple to translocate two ions in "parallel" at alkaline pH. In the second "serial" model, each monomer transports two ions, and translocation by one monomer allosterically promotes translocation by the paired monomer in opposite direction. We conclude that a large fraction of mammalian Na/H activity may occur with a 2Na/2H stoichiometry.

Models with Plants, Microorganisms and Viruses for Basic Research in Homeopathy

Most criticism about homeopathy concerns the lack of a scientific basis and theoretical models. In order to be accepted as a valid part of medical practice, a wellstructured research strategy for homeopathy is needed. This is often hampered by methodological problems as well as by gross underinvestment in the required academic resources. Fundamental research could make important contributions to our understanding of the homeopathic and high dilutions mechanisms of action. Since the pioneering works of Kolisko on wheat germination (Kolisko, 1923) and Junker on growth of microorganisms (paramecium, yeast, fungi) (Junker, 1928), a number of experiments have been performed either with healthy organisms (various physiological aspects of growth) or with artificially diseased organisms, which may react more markedly to homeopathic treatments than healthy ones. In the latter case, the preliminary stress may be either abiotic, e.g. heavy metals, or biotic, e.g. fungal and viral pathogens or nematode infection. Research has also been carried out into the applicability of homeopathic principles to crop growth and disease control (agrohomeopathy): because of the extreme dilutions used, the environmental impact is low and such treatments are well suited to the holistic approach of sustainable agriculture (Betti et al., 2006). Unfortunately, as Scofield reported in an extensive critical review (Scofield, 1984), there is little firm evidence to support the reliability of the reported results, due to poor experimental methodology and inadequate statistical analysis. Moreover, since there is no agricultural homeopathic pharmacopoeia, much work is required to find suitable remedies, potencies and dose levels.

Hotshots, hot spots, and female preference: exploring lek formation models with a bower-building cichlid fish

In many animals, males congregate in leks that females visit for the sole purpose of mating. We observed male and female behavior on 3 different-sized leks of the bower-building cichlid fish Nyassachromis cf. microcephalus to test predictions of 3 prominent lek models: the "hotshot," "hot spot," and "female preference" models. In this system, we were able to refine these predictions by distinguishing between indirect mate choice, by which females restrict their set of potential mates in the absence of individual male assessment, and direct mate choice, by which females assess males and their territories through dyadic behavioral interactions. On no lek were males holding central territories favored by indirect or direct mate choice, contrary to the prediction of the hotshot model that leks form because inferior males establish territories surrounding hotshot males preferred by females. Average female encounter rate of males increased with lek size, a pattern typically interpreted as evidence that leks form through female preference for lekking males, rather than because males congregate in hot spots of high female density. Female propensity to engage in premating behavior once courted did not increase with lek size, suggesting female preference for males on larger leks operated through indirect choice rather than direct choice based on individual assessment. The frequency of male-male competitive interactions increased with lek size, whereas their foraging rate decreased, implying a cost to males maintaining territories on larger leks. Together these data most strongly support the female preference model, where females may benefit through indirect mate choice for males able to meet the competitive cost of occupying larger leks.

Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments

This paper studies the energy-efficiency and service characteristics of a recently developed energy-efficient MAC protocol for wireless sensor networks in simulation and on a real sensor hardware testbed. This opportunity is seized to illustrate how simulation models can be verified by cross-comparing simulation results with real-world experiment results. The paper demonstrates that by careful calibration of simulation model parameters, the inevitable gap between simulation models and real-world conditions can be reduced. It concludes with guidelines for a methodology for model calibration and validation of sensor network simulation models.

Flavor-phenomenology of two-Higgs-doublet models with generic Yukawa structure

In this article, we perform an extensive study of flavor observables in a two-Higgs-doublet model with generic Yukawa structure (of type III). This model is interesting not only because it is the decoupling limit of the minimal supersymmetric standard model but also because of its rich flavor phenomenology which also allows for sizable effects not only in flavor-changing neutral-current (FCNC) processes but also in tauonic B decays. We examine the possible effects in flavor physics and constrain the model both from tree-level processes and from loop observables. The free parameters of the model are the heavy Higgs mass, tanβ (the ratio of vacuum expectation values) and the “nonholomorphic” Yukawa couplings ϵfij(f=u,d,ℓ). In our analysis we constrain the elements ϵfij in various ways: In a first step we give order of magnitude constraints on ϵfij from ’t Hooft’s naturalness criterion, finding that all ϵfij must be rather small unless the third generation is involved. In a second step, we constrain the Yukawa structure of the type-III two-Higgs-doublet model from tree-level FCNC processes (Bs,d→μ+μ−, KL→μ+μ−, D¯¯¯0→μ+μ−, ΔF=2 processes, τ−→μ−μ+μ−, τ−→e−μ+μ− and μ−→e−e+e−) and observe that all flavor off-diagonal elements of these couplings, except ϵu32,31 and ϵu23,13, must be very small in order to satisfy the current experimental bounds. In a third step, we consider Higgs mediated loop contributions to FCNC processes [b→s(d)γ, Bs,d mixing, K−K¯¯¯ mixing and μ→eγ] finding that also ϵu13 and ϵu23 must be very small, while the bounds on ϵu31 and ϵu32 are especially weak. Furthermore, considering the constraints from electric dipole moments we obtain constrains on some parameters ϵu,ℓij. Taking into account the constraints from FCNC processes we study the size of possible effects in the tauonic B decays (B→τν, B→Dτν and B→D∗τν) as well as in D(s)→τν, D(s)→μν, K(π)→eν, K(π)→μν and τ→K(π)ν which are all sensitive to tree-level charged Higgs exchange. Interestingly, the unconstrained ϵu32,31 are just the elements which directly enter the branching ratios for B→τν, B→Dτν and B→D∗τν. We show that they can explain the deviations from the SM predictions in these processes without fine-tuning. Furthermore, B→τν, B→Dτν and B→D∗τν can even be explained simultaneously. Finally, we give upper limits on the branching ratios of the lepton flavor-violating neutral B meson decays (Bs,d→μe, Bs,d→τe and Bs,d→τμ) and correlate the radiative lepton decays (τ→μγ, τ→eγ and μ→eγ) to the corresponding neutral current lepton decays (τ−→μ−μ+μ−, τ−→e−μ+μ− and μ−→e−e+e−). A detailed Appendix contains all relevant information for the considered processes for general scalar-fermion-fermion couplings.

O(N) Models with Topological Lattice Actions

A variety of lattice discretisations of continuum actions has been considered, usually requiring the correct classical continuum limit. Here we discuss “weird” lattice formulations without that property, namely lattice actions that are invariant under most continuous deformations of the field configuration, in one version even without any coupling constants. It turns out that universality is powerful enough to still provide the correct quantum continuum limit, despite the absence of a classical limit, or a perturbative expansion. We demonstrate this for a set of O(N) models (or non-linear σ-models). Amazingly, such “weird” lattice actions are not only in the right universality class, but some of them even have practical benefits, in particular an excellent scaling behaviour.

Exact moment calculations for genetic models with migration, mutation, and drift

Using properties of moment stationarity we develop exact expressions for the mean and covariance of allele frequencies at a single locus for a set of populations subject to drift, mutation, and migration. Some general results can be obtained even for arbitrary mutation and migration matrices, for example: (1) Under quite general conditions, the mean vector depends only on mutation rates, not on migration rates or the number of populations. (2) Allele frequencies covary among all pairs of populations connected by migration. As a result, the drift, mutation, migration process is not ergodic when any finite number of populations is exchanging genes. in addition, we provide closed form expressions for the mean and covariance of allele frequencies in Wright's finite-island model of migration under several simple models of mutation, and we show that the correlation in allele frequencies among populations can be very large for realistic rates of mutation unless an enormous number of populations are exchanging genes. As a result, the traditional diffusion approximation provides a poor approximation of the stationary distribution of allele frequencies among populations. Finally, we discuss some implications of our results for measures of population structure based on Wright's F-statistics.

Using spatial linear models with SAR and CAR structure to examine Texas lung cancer incidence rates

Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^