Formulating Mixed Models for Experiments, Including Longitudinal Experiments

Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

Inheritance of growth habit detected by genetic linkage analysis using microsatellites in the common bean (Phaseolus vulgaris L.)

The genetic linkage map for the common bean (Phaseolus vulgaris L.) is a valuable tool for breeding programs. Breeders provide new cultivars that meet the requirements of farmers and consumers, such as seed color, seed size, maturity, and growth habit. A genetic study was conducted to examine the genetics behind certain qualitative traits. Growth habit is usually described as a recessive trait inherited by a single gene, and there is no consensus about the position of the locus. The aim of this study was to develop a new genetic linkage map using genic and genomic microsatellite markers and three morphological traits: growth habit, flower color, and pod tip shape. A mapping population consisting of 380 recombinant F10 lines was generated from IAC-UNA x CAL143. A total of 871 microsatellites were screened for polymorphisms among the parents, and a linkage map was obtained with 198 mapped microsatellites. The total map length was 1865.9 cM, and the average distance between markers was 9.4 cM. Flower color and pod tip shape were mapped and segregated at Mendelian ratios, as expected. The segregation ratio and linkage data analyses indicated that the determinacy growth habit was inherited as two independent and dominant genes, and a genetic model is proposed for this trait.

Allochronic taxa as an alternative model to explain circumantarctic disjunctions

Most biogeographical studies propose that southern temperate faunal disjunctions are either the result of vicariance of taxa originated in Gondwana or the result of transoceanic dispersal of taxa originated after the breakup of Gondwana. The aim of this paper is to show that this is a false dichotomy. Antarctica retained a mild climate until mid-Cenozoic and had lasting connections, notably with southern South America and Australia. Both taxa originally Gondwanan and taxa secondarily on Gondwanan areas were subjected to tectonic-induced vicariance, and there is no need to invoke ad hoc transoceanic dispersal, even for post-Gondwanan taxa. These different elements with circumantarctic distributions are here called `allochronic taxa` - taxa presently occupying the same area, but whose presence in that area does not belong to the same time period. This model allows accommodation of conflicting sources of evidence now available for many groups with circumantarctic distributions. The fact that the species from both layers are mixed up in the current biodiversity implies the need to use additional sources of evidence - such as biogeographical, palaeontological, geological and molecular - to discriminate which are the original Gondwanan and which are post-Gondwanan elements in austral landmasses.

Hyaluronidase Behavior at the Air/Liquid and Air/Lipid Interfaces and Improved Enzymatic Activity by Its Immobilization in a Biomembrane Model

Bovine testicular hyalurphidase (BT-HAase), a tetrameric enzyme responsible for randomly hyaluronic acid, catalytic hydrolysis, was successfully immobilized on Langmuir- Blodgett films prepared with the sodium salt of dihexadacylphosphoric acid, (DHP-Zn(II)) ending with dipalmitoylphosphatidylcholine, DPPC. Data of protein, adsorption at the air-liquid interface by means of pendant drop shipe analysis and interaction of the protein with Langmuir monolayers of DPPC, using a Langmuir trough, have provided information. about the conditions to be used in the protein immobilization. The dynamic surface pressure curves obtained from pendant drop experiments for the enzyme in buffer solutions indicate that, within the range of concentration investigated in this study, the enzyme exhibits the largest induction time at 5 mu g L(-1) attributed to diffusion processes. Nevertheless, it seems that, at this concentration, the most probable conformation should be the one which occupies the smallest area at pi -> 0. The surface pressure (pi) area curves obtained for BT-HAase and mixed DPPC- BT-HAase monolayers reveal the presence of the enzyme at the air-lipid interface up to 45 mN m(-1). Tests of enzymatic activity, using hyaluronic acid, HA, as the substrate, showed an increase of activity compared to the homogeneous medium. A simplified model of protein insertion into the lipid matrix is used to explain the obtained results.

Chitosan as a Bioadhesive Agent Between Porphyrins and Phospholipids in a Biomembrane Model

Porphyrins are currently used in photodynamic therapy as photosensitizers. In this paper we studied the interaction of two charged porphyrins, 5, 10, 15, 20-mesotetrakis(N-metyl-4-pyridyl) porphyrin, (TMPyP/chloride salt) cationic, and 5, 10, 15, 20-meso-tetrakis(sulfonatophenyl) porphyrin, (TPPS(4)/sodium salt) anionic, nanoassembled in phospholipid Langmuir monolayers and Langmuir-Blodgett films. Furthermore, we used chitosan to mediate the interaction between the porphyrins and the model membrane, aiming to understand the role of the polysaccharide in a molecular level. The effect of the interaction of the photosensitizers on the fluidity of the lipid monolayer was investigated by using dilatational surface elasticity. We also used photoluminescence (PL) spectroscopy to identify the porphyrins adsorbed in the phospholipid films. We observed an expansion of the monolayer promoted by the adsorption of the porphyrins into the lipid-air interface which was more pronounced in the case of TMPyP, as a consequence of a strong electrostatic interaction with the anionic monolayer. The chitosan promoted a higher adsorption of the porphyrins on the phospholipid monolayers and enabled the porphyrin to stay in its monomeric form (as confirmed by PL spectroscopy), thus demonstrating that chitosan can be pointed out as a potential photosensitizer delivery system in photodynamic therapy.

Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication

Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

Experimental tuberculosis: Designing a better model to test vaccines against tuberculosis

Experimental models of infection are good tools for establishing immunological parameters that have an effect on the host-pathogen relationship and also for designing new vaccines and immune therapies. In this work, we evaluated the evolution of experimental tuberculosis in mice infected with increasing bacterial doses or via distinct routes. We showed that mice infected with low bacterial doses by the intratracheal route were able to develop a progressive infection that was proportional to the inoculum size. In the initial phase of disease, mice developed a specific Th1-driven immune response independent of inoculum concentration. However, in the late phase, mice infected with higher concentrations exhibited a mixed Th1/Th2 response, while mice infected with lower concentrations sustained the Th1 pattern. Significant IL-10 concentrations and a more preeminent T regulatory cell recruitment were also detected at 70 days post-infection with high bacterial doses. These results suggest that mice infected with higher concentrations of bacilli developed an immune response similar to the pattern described for human tuberculosis wherein patients with progressive tuberculosis exhibit a down modulation of IFN-gamma production accompanied by increased levels of IL-4. Thus, these data indicate that the experimental model is important in evaluating the protective efficacy of new vaccines and therapies against tuberculosis. (C) 2010 Elsevier Ltd. All rights reserved.

STUDY OF THE EQUATORIAL ATLANTIC OCEAN MIXING LAYER USING A ONE-DIMENSIONAL TURBULENCE MODEL

The General Ocean Turbulence Model (GOTM) is applied to the diagnostic turbulence field of the mixing layer (ML) over the equatorial region of the Atlantic Ocean. Two situations were investigated: rainy and dry seasons, defined, respectively, by the presence of the intertropical convergence zone and by its northward displacement. Simulations were carried out using data from a PIRATA buoy located on the equator at 23 degrees W to compute surface turbulent fluxes and from the NASA/GEWEX Surface Radiation Budget Project to close the surface radiation balance. A data assimilation scheme was used as a surrogate for the physical effects not present in the one-dimensional model. In the rainy season, results show that the ML is shallower due to the weaker surface stress and stronger stable stratification; the maximum ML depth reached during this season is around 15 m, with an averaged diurnal variation of 7 m depth. In the dry season, the stronger surface stress and the enhanced surface heat balance components enable higher mechanical production of turbulent kinetic energy and, at night, the buoyancy acts also enhancing turbulence in the first meters of depth, characterizing a deeper ML, reaching around 60 m and presenting an average diurnal variation of 30 m.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

Influence diagnostics in nonlinear mixed-effects elliptical models

In this work we propose and analyze nonlinear elliptical models for longitudinal data, which represent an alternative to gaussian models in the cases of heavy tails, for instance. The elliptical distributions may help to control the influence of the observations in the parameter estimates by naturally attributing different weights for each case. We consider random effects to introduce the within-group correlation and work with the marginal model without requiring numerical integration. An iterative algorithm to obtain maximum likelihood estimates for the parameters is presented, as well as diagnostic results based on residual distances and local influence [Cook, D., 1986. Assessment of local influence. journal of the Royal Statistical Society - Series B 48 (2), 133-169; Cook D., 1987. Influence assessment. journal of Applied Statistics 14 (2),117-131; Escobar, L.A., Meeker, W.Q., 1992, Assessing influence in regression analysis with censored data, Biometrics 48, 507-528]. As numerical illustration, we apply the obtained results to a kinetics longitudinal data set presented in [Vonesh, E.F., Carter, R.L., 1992. Mixed-effects nonlinear regression for unbalanced repeated measures. Biometrics 48, 1-17], which was analyzed under the assumption of normality. (C) 2009 Elsevier B.V. All rights reserved.

Antiferromagnetic spherical spin-glass model

We study the thermodynamic properties and the phase diagrams of a multi-spin antiferromagnetic spherical spin-glass model using the replica method. It is a two-sublattice version of the ferromagnetic spherical p-spin glass model. We consider both the replica-symmetric and the one-step replica-symmetry-breaking solutions, the latter being the most general solution for this model. We find paramagnetic, spin-glass, antiferromagnetic and mixed or glassy antiferromagnetic phases. The phase transitions are always of second order in the thermodynamic sense, but the spin-glass order parameter may undergo a discontinuous change.

Interaction of a C-terminal peptide of Bos taurus diacylglycerol acyltransferase 1 with model membranes

Diacylglycerol acyltransferase 1 (DGAT1) catalyzes the final and dedicated step in the synthesis of triacylglycerol, which is believed to involve the lipids oleoyl coenzyme A (OCoA) and dioleoyl-sn-glycerol (DOG) as substrates. In this work we investigated the interaction of a specific peptide, referred to as SIT2, on the C-terminal of DGAT1 (HKWCIRHFYKP) with model membranes made with OCoA and DOG in Langmuir monolayers and liposomes. According to the circular dichroism and fluorescence data, conformational changes on SIT2 were seen only on liposomes containing OCoA and DOG. In Langmuir monolayers, SIT2 causes the isotherms of neat OCoA and DOG monolayers to be expanded, but has negligible effect on mixed monolayers of OCoA and DOG. This synergistic interaction between SIT2 and DOG + OCoA may be rationalized in terms of a molecular model in which SIT2 may serve as a linkage between the two lipids. Our results therefore provide molecular-level evidence for the interaction between this domain and the substrates OCoA and DOG for the synthesis of triacylglycerol. (C) 2009 Elsevier B.V. All rights reserved.

Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.

On estimation and influence diagnostics for the Grubbs` model under heavy-tailed distributions

The Grubbs` measurement model is frequently used to compare several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations, whereas scale mixtures of normal distributions have been an interesting alternative to produce robust estimates, keeping the elegancy and simplicity of the maximum likelihood theory. The aim of this paper is to develop an EM-type algorithm for the parameter estimation, and to use the local influence method to assess the robustness aspects of these parameter estimates under some usual perturbation schemes, In order to identify outliers and to criticize the model building we use the local influence procedure in a Study to compare the precision of several thermocouples. (C) 2008 Elsevier B.V. All rights reserved.

Local Influence Analysis for Skew-Normal Linear Mixed Models

In this article, we consider local influence analysis for the skew-normal linear mixed model (SN-LMM). As the observed data log-likelihood associated with the SN-LMM is intractable, Cook`s well-known approach cannot be applied to obtain measures of local influence. Instead, we develop local influence measures following the approach of Zhu and Lee (2001). This approach is based on the use of an EM-type algorithm and is measurement invariant under reparametrizations. Four specific perturbation schemes are discussed. Results obtained for a simulated data set and a real data set are reported, illustrating the usefulness of the proposed methodology.