Statistical modeling of protein lysate array data

The protein lysate array is an emerging technology for quantifying the protein concentration ratios in multiple biological samples. It is gaining popularity, and has the potential to answer questions about post-translational modifications and protein pathway relationships. Statistical inference for a parametric quantification procedure has been inadequately addressed in the literature, mainly due to two challenges: the increasing dimension of the parameter space and the need to account for dependence in the data. Each chapter of this thesis addresses one of these issues. In Chapter 1, an introduction to the protein lysate array quantification is presented, followed by the motivations and goals for this thesis work. In Chapter 2, we develop a multi-step procedure for the Sigmoidal models, ensuring consistent estimation of the concentration level with full asymptotic efficiency. The results obtained in this chapter justify inferential procedures based on large-sample approximations. Simulation studies and real data analysis are used to illustrate the performance of the proposed method in finite-samples. The multi-step procedure is simpler in both theory and computation than the single-step least squares method that has been used in current practice. In Chapter 3, we introduce a new model to account for the dependence structure of the errors by a nonlinear mixed effects model. We consider a method to approximate the maximum likelihood estimator of all the parameters. Using the simulation studies on various error structures, we show that for data with non-i.i.d. errors the proposed method leads to more accurate estimates and better confidence intervals than the existing single-step least squares method.

Accelerating retreat and high-elevation thinning of glaciers in central Spitsbergen

Svalbard is a heavily glacier-covered archipelago in the Arctic. Dickson Land (DL), in the central part of the largest island, Spitsbergen, is relatively arid, and as a result, glaciers there are relatively small and restricted mostly to valleys and cirques. This study presents a comprehensive analysis of glacier changes in DL based on inventories compiled from topographic maps and digital elevation models for the Little Ice Age maximum (LIA), the 1960s, 1990 and 2009/11. Total glacier area decreased by ~38 % since the LIA maximum, and front retreat has increased over the study period. Recently, most of the local glaciers have been consistently thinning in all elevation bands, in contrast to larger Svalbard ice masses which remain closer to balance. The mean 1990–2009/11 geodetic mass balance of glaciers in DL is among the most negative from the Svalbard regional means known from the literature.

Knowledge about dietary fibres (KADF): development and validation of an evaluation instrument through structural equation modelling (SEM)

Objectives: Because there is scientific evidence that an appropriate intake of dietary fibre should be part of a healthy diet, given its importance in promoting health, the present study aimed to develop and validate an instrument to evaluate the knowledge of the general population about dietary fibres. Study design: The present study was a cross sectional study. Methods: The methodological study of psychometric validation was conducted with 6010 participants, residing in ten countries from 3 continents. The instrument is a questionnaire of self-response, aimed at collecting information on knowledge about food fibres. For exploratory factor analysis (EFA) was chosen the analysis of the main components using varimax orthogonal rotation and eigenvalues greater than 1. In confirmatory factor analysis by structural equation modelling (SEM) was considered the covariance matrix and adopted the Maximum Likelihood Estimation algorithm for parameter estimation. Results: Exploratory factor analysis retained two factors. The first was called Dietary Fibre and Promotion of Health (DFPH) and included 7 questions that explained 33.94 % of total variance ( = 0.852). The second was named Sources of Dietary Fibre (SDF) and included 4 questions that explained 22.46% of total variance ( = 0.786). The model was tested by SEM giving a final solution with four questions in each factor. This model showed a very good fit in practically all the indexes considered, except for the ratio 2/df. The values of average variance extracted (0.458 and 0.483) demonstrate the existence of convergent validity; the results also prove the existence of discriminant validity of the factors (r2 = 0.028) and finally good internal consistency was confirmed by the values of composite reliability (0.854 and 0.787). Conclusions: This study allowed validating the KADF scale, increasing the degree of confidence in the information obtained through this instrument in this and in future studies.

Modeling height-diameter relationship in pinus pinaster ait. in the forest intervention zone of Lomba, NE-Portugal

In this work, the relationship between diameter at breast height (d) and total height (h) of individual-tree was modeled with the aim to establish provisory height-diameter (h-d) equations for maritime pine (Pinus pinaster Ait.) stands in the Lomba ZIF, Northeast Portugal. Using data collected locally, several local and generalized h-d equations from the literature were tested and adaptations were also considered. Model fitting was conducted by using usual nonlinear least squares (nls) methods. The best local and generalized models selected, were also tested as mixed models applying a first-order conditional expectation (FOCE) approximation procedure and maximum likelihood methods to estimate fixed and random effects. For the calibration of the mixed models and in order to be consistent with the fitting procedure, the FOCE method was also used to test different sampling designs. The results showed that the local h-d equations with two parameters performed better than the analogous models with three parameters. However a unique set of parameter values for the local model can not be used to all maritime pine stands in Lomba ZIF and thus, a generalized model including covariates from the stand, in addition to d, was necessary to obtain an adequate predictive performance. No evident superiority of the generalized mixed model in comparison to the generalized model with nonlinear least squares parameters estimates was observed. On the other hand, in the case of the local model, the predictive performance greatly improved when random effects were included. The results showed that the mixed model based in the local h-d equation selected is a viable alternative for estimating h if variables from the stand are not available. Moreover, it was observed that it is possible to obtain an adequate calibrated response using only 2 to 5 additional h-d measurements in quantile (or random) trees from the distribution of d in the plot (stand). Balancing sampling effort, accuracy and straightforwardness in practical applications, the generalized model from nls fit is recommended. Examples of applications of the selected generalized equation to the forest management are presented, namely how to use it to complete missing information from forest inventory and also showing how such an equation can be incorporated in a stand-level decision support system that aims to optimize the forest management for the maximization of wood volume production in Lomba ZIF maritime pine stands.

Modelos autorregressivos com valores inteiros não negativos : aplicação em séries económicas de Cabo Verde

No estudo de séries temporais, os processos estocásticos usuais assumem que as distribuições marginais são contínuas e, em geral, não são adequados para modelar séries de contagem, pois as suas características não lineares colocam alguns problemas estatísticos, principalmente na estimação dos parâmetros. Assim, investigou-se metodologias apropriadas de análise e modelação de séries com distribuições marginais discretas. Neste contexto, Al-Osh and Alzaid (1987) e McKenzie (1988) introduziram na literatura a classe dos modelos autorregressivos com valores inteiros não negativos, os processos INAR. Estes modelos têm sido frequentemente tratados em artigos científicos ao longo das últimas décadas, pois a sua importância nas aplicações em diversas áreas do conhecimento tem despertado um grande interesse no seu estudo. Neste trabalho, após uma breve revisão sobre séries temporais e os métodos clássicos para a sua análise, apresentamos os modelos autorregressivos de valores inteiros não negativos de primeira ordem INAR (1) e a sua extensão para uma ordem p, as suas propriedades e alguns métodos de estimação dos parâmetros nomeadamente, o método de Yule-Walker, o método de Mínimos Quadrados Condicionais (MQC), o método de Máxima Verosimilhança Condicional (MVC) e o método de Quase Máxima Verosimilhança (QMV). Apresentamos também um critério automático de seleção de ordem para modelos INAR, baseado no Critério de Informação de Akaike Corrigido, AICC, um dos critérios usados para determinar a ordem em modelos autorregressivos, AR. Finalmente, apresenta-se uma aplicação da metodologia dos modelos INAR em dados reais de contagem relativos aos setores dos transportes marítimos e atividades de seguros de Cabo Verde.

Modelos linear e não linear em análises genéticas para sobrevivência de crias de ovinos da raça Santa Inês.

Resumo: Registros de sobrevivência do nascimento ao desmame de 3846 crias de ovinos da raça Santa Inês foram analisados por modelos de reprodutor linear e não linear (modelo de limiar), para estimar componentes de variância e herdabilidade. Os modelos usados para sobrevivência, analisada como característica da cria, incluíram os efeitos fixos de sexo, da combinação tipo de nascimento-criação da cria e da idade da ovelha ao parto, efeito da covariável peso da cria ao nascer e efeitos aleatórios de reprodutor, da classe rebanho-ano-estação e do resíduo. Componentes de variância para o modelo linear foram estimados pelo método da máxima verossimilhança restrita (REML) e para o modelo não linear por uma aproximação da máxima verossimilhança marginal (MML), pelo programa CMMAT2. O coeficiente de herdabilidade (h2) estimado pelo modelo de limiar foi de 0,29, e pelo modelo linear, 0,14. A correlação de ordem de Spearman entre as capacidades de transmissão dos reprodutores, com base nos dois modelos foi de 0,96. As estimativas de h2 obtidas indicam a possibilidade de se obter, por seleção, ganho genético para sobrevivência. [Linear and nonlinear models in genetic analyses of lamb survival in the Santa Inês hair sheep breed]. Abstract: Records of 3,846 lambs survival from birth to weaning of Santa Inês hair sheep breed, were analyzed by linear and non linear sire models (threshold model) to estimate variance components and heritability (h2). The models that were used to analyze survival, considered in this study as a lamb trait, included the fixed effects of sex of the lamb, combination of type of birth-rearing of lamb, and age of ewe, birth weight of lamb as covariate, and random effects of sire, herd-year-season and residual. Variance components were obtained using restricted maximum likelihood (REML), in linear model and marginal maximum likelihood in threshold model through CMMAT2 program. Estimate of heritability (h2) obtained by threshold model was 0.29 and by linear model was 0.14. Rank correlation of Spearman, between sire solutions based on the two models was 0.96. The obtained estimates in this study indicate that it is possible to acquire genetic gain to survival by selection.

Keeping Variables within Bounds: Using Information between Observations

This research develops an econometric framework to analyze time series processes with bounds. The framework is general enough that it can incorporate several different kinds of bounding information that constrain continuous-time stochastic processes between discretely-sampled observations. It applies to situations in which the process is known to remain within an interval between observations, by way of either a known constraint or through the observation of extreme realizations of the process. The main statistical technique employs the theory of maximum likelihood estimation. This approach leads to the development of the asymptotic distribution theory for the estimation of the parameters in bounded diffusion models. The results of this analysis present several implications for empirical research. The advantages are realized in the form of efficiency gains, bias reduction and in the flexibility of model specification. A bias arises in the presence of bounding information that is ignored, while it is mitigated within this framework. An efficiency gain arises, in the sense that the statistical methods make use of conditioning information, as revealed by the bounds. Further, the specification of an econometric model can be uncoupled from the restriction to the bounds, leaving the researcher free to model the process near the bound in a way that avoids bias from misspecification. One byproduct of the improvements in model specification is that the more precise model estimation exposes other sources of misspecification. Some processes reveal themselves to be unlikely candidates for a given diffusion model, once the observations are analyzed in combination with the bounding information. A closer inspection of the theoretical foundation behind diffusion models leads to a more general specification of the model. This approach is used to produce a set of algorithms to make the model computationally feasible and more widely applicable. Finally, the modeling framework is applied to a series of interest rates, which, for several years, have been constrained by the lower bound of zero. The estimates from a series of diffusion models suggest a substantial difference in estimation results between models that ignore bounds and the framework that takes bounding information into consideration.

An alternative methodology for fitting selectivity curves to pre-defined distributions

A non-linear least-squares methodology for simultaneously estimating parameters of selectivity curves with a pre-defined functional form, across size classes and mesh sizes, using catch size frequency distributions, was developed based on the model of Kirkwood and Walker [Kirkwood, G.P., Walker, T.L, 1986. Gill net selectivities for gummy shark, Mustelus antarcticus Gunther, taken in south-eastern Australian waters. Aust. J. Mar. Freshw. Res. 37, 689-697] and [Wulff, A., 1986. Mathematical model for selectivity of gill nets. Arch. Fish Wiss. 37, 101-106]. Observed catches of fish of size class I in mesh m are modeled as a function of the estimated numbers of fish of that size class in the population and the corresponding selectivities. A comparison was made with the maximum likelihood methodology of [Kirkwood, G.P., Walker, T.I., 1986. Gill net selectivities for gummy shark, Mustelus antarcticus Gunther, taken in south-eastern Australian waters. Aust. J. Mar. Freshw. Res. 37, 689-697] and [Wulff, A., 1986. Mathematical model for selectivity of gill nets. Arch. Fish Wiss; 37, 101-106], using simulated catch data with known selectivity curve parameters, and two published data sets. The estimated parameters and selectivity curves were generally consistent for both methods, with smaller standard errors for parameters estimated by non-linear least-squares. The proposed methodology is a useful and accessible alternative which can be used to model selectivity in situations where the parameters of a pre-defined model can be assumed to be functions of gear size; facilitating statistical evaluation of different models and of goodness of fit. (C) 1998 Elsevier Science B.V.

Comparative fixed gear studies in the Cyclades (Aegean Sea): size selectivity of small-hook longlines and monofilament gill nets

Fishing trials with monofilament gill nets and longlines using small hooks were carried out at the same fishing grounds in Cyclades (Aegean Sea) over 1 year. Four sizes of MUSTAD brand, round bent, flatted sea hooks (Quality 2316 DT, numbers 15, 13, 12 and 11) and four mesh sizes of 22, 24, 26 and 28 turn nominal bar length monofilament gill nets were used. Significant differences in the catch size frequency distributions of the two gears were found for four out of five of the most important species caught by both the gears (Diplodus annularis, Diplodus vulgaris, Pagellus erythrinus, Scorpaena porcus and Serranus cabrilla), with longlines catching larger fish and a wider size range than gill nets. Whereas longline catch size frequency distributions for most species for the different hook sizes were generally highly overlapped, suggesting little or no differences in size selectivity, gill net catch size frequency distributions clearly showed size selection, with larger mesh sizes catching larger fish. A variety of models were fitted to the gill net data, with the lognormal providing the best fit in most cases. A maximum likelihood method was also used to estimate the parameters of the logistic model for the longline data. Because of the highly overlapped longline catch size frequency distributions parameters could only be estimated for two species. This study shows that the two static gears have different impacts in terms of size selection. This information will be useful for the more effective management of these small-scale, multi-species and multi-gear fisheries. (C) 2002 Elsevier Science B.V. All rights reserved.

Quantifying the roles of competing static gears: comparative selectivity of longlines and monofilament gill nets in a multi-species fishery of the Algarve (southern Portugal)

Fishing trials with monofilament gill nets and longlines using small hooks were carried out in Algarve waters (southern Portugal) over a one-year period. Four hook sizes of "Mustad" brand, round bent, flatted sea hooks (Quality 2316 DT, numbers 15, 13, 12 and 11) and four mesh sizes of 25, 30, 35 and 40 mm (bar length) monofilament gill nets were used. Commercially valuable sea breams dominated the longline catches while small pelagics were relatively more important in the gill nets. Significant differences in the catch size frequency distributions of the two gears were found for all the most important species caught by both gears (Boops boops, Diplodus bellottii, Diplodus vulgaris, Pagellus acarne, Pagellus erythrinus, Spondyiosoma cantharus, Scomber japonicus and Scorpaena notata), with longlines catching larger fish and a wider size range than nets. Whereas longline catch size frequency distributions for most species for the different hook sizes were generally highly overlapped, suggesting little or no differences in size selectivity, gill net catch size frequency distributions clearly showed size selection. A variety of models were fitted to the gill net and hook data using the SELECT method, while the parameters of the logistic model were estimated by maximum likelihood for the longline data. The bi-normal model gave the best fits for most of the species caught with gill nets, while the logistic model adequately described hook selectivity. The results of this study show that the two static gears compete for many of the same species and have different impacts in terms of catch composition and size selectivity. This information will I;e useful for the improved management of these small-scale fisheries in which many different gears compete for scarce resources.

Size selectivity of trammel nets in southern European small-scale fisheries

Trammel net size selectivity was studied for the most important metiers in four southern European areas: the Cantabrian Sea (Atlantic, Basque Country, Spain), the Algarve (Atlantic, southern Portugal), the Gulf of Cadiz (Atlantic, Spain) and the Cyclades Islands (Mediterranean, Aegean Sea, Greece). These metiers were: cuttlefish (Sepia officinalis) and soles (Solea senegalensis, Microchirus azevia, Synaptura lusitanica) in the Algarve and the Gulf of Cadiz, sole (Solea solea) in the Cantabrian Sea and mixed fin-fish in the Cyclades. In each area, experimental trammel nets of six different types (combinations of two large outer panel mesh sizes and three small inner panel meshes) were constructed. Fishing trials were carried out on a seasonal basis (four seasons in the Cantabrian Sea, Algarve and Cyclades and two seasons in the Gulf of Cadiz) with chartered commercial fishing vessels. Overall, size selectivity was estimated for 17 out of 28 species for which sufficient data were available. Trammel nets generally caught a wide size range of the most important species, with length frequency distributions that were skewed to the right and/or bi-modal. In many cases the length frequency distributions of the different nets were highly overlapped. The Kolmogorov-Smirnov test also showed that the large outer panel meshes generally had no effect in terms of size selectivity, while the opposite was true for the small inner panel ones. Six different selectivity models (normal scale, normal location, gamma, log-normal, bi-modal and gamma semi-Wileman) were fitted to data for the most abundant species in the four areas. For fish, the bi-modal model provided the best fits for the majority of the data sets, with the uni-modal models giving poor fits in most cases. For Sepia officinalis, where trammelling or pocketing was the method of capture in 100% of the cases, the logistic model fitted by maximum likelihood was judged to be more appropriate for describing the size selective properties of the trammel nets. Our results, which are among the first ones on trammel net selectivity in European waters, will be useful for evaluating the impacts of competing gear for the socio-economically important small-scale static gear fisheries. (c) 2006 Elsevier B.V All rights reserved.

VALIDATION STUDY OF HEALTH BELIEFS SCALE

Introduction: The Health Belief Scale is a questionnaire used to assess a wide range of beliefs related to health. The objective of this study was to undertake construction and culturally adapt the Health Belief Scale (HBS) to the Portuguese language and to test its reliability and validity. Methods: This new version was obtained with forward/backward translations, consensus panels and a pre-test, having been inspired by some of the items from “Canada’s Health Promotion Survey” and the “European Health and Behaviour Survey”, with the inclusion of new items about food-related beliefs. The Portuguese version of Health Belief Scale and a form for the characteristics of the participants were applied to 849 Portuguese adolescents. Results: Reliability was good with a Cronbach’s alpha coeficient of 0.867, and an intraclass correlation coeficient (ICC) of 0.95. Corrected item-total coeficients ranged from 0.301 to 0.620 and weighted kappa coeficients ranged from 0.72 to 0.93 for the total scale items. We obtained a scale composed of 13 items divided into ive factors (smoking and alcohol belief, food belief, sexual belief, physical and sporting belief, and social belief), which explain 57.97% of the total variance. Conclusions: The scale exhibited suitable psychometric properties, in terms of internal consistency, reproducibility and construct validity. It can be used in various areas of research.

Effect of inclusion or non-inclusion of short lactations and cow and/or dam genetic group on genetic evaluation of Girolando dairy cattle.

The objective of this study was to evaluate the effects of inclusion or non-inclusion of short lactations and cow (CGG) and/or dam (DGG) genetic group on the genetic evaluation of 305-day milk yield (MY305), age at first calving (AFC), and first calving interval (FCI) of Girolando cows. Covariance components were estimated by the restricted maximum likelihood method in an animal model of single trait analyses. The heritability estimates for MY305, AFC, and FCI ranged from 0.23 to 0.29, 0.40 to 0.44, and 0.13 to 0.14, respectively, when short lactations were not included, and from 0.23 to 0.28, 0.39 to 0.43, and 0.13 to 0.14, respectively, when short lactations were included. The inclusion of short lactations caused little variation in the variance components and heritability estimates of traits, but their non-inclusion resulted in the re-ranking of animals. Models with CGG or DGG fixed effects had higher heritability estimates for all traits compared with models that consider these two effects simultaneously. We recommend using the model with fixed effects of CGG and inclusion of short lactations for the genetic evaluation of Girolando cattle.

Is the maximum velocity of carboxylation (Vcmax) well adjusted for deciduous shrubs in DGVMs: a case study for the Caatinga Biome in Brazil.

Vcmax is the rate of maximum velocity of carboxylation of plants and is considered one of the most critical parameters for changes in vegetation in face of global changes and it has a direct impact on gross primary productivity. Physiological processes are considered the main sources of uncertainties in dynamic global vegetation models (DGVMs). The Caatinga biome, in the semiarid region of northeastern Brazil, is extremely important due to its biodiversity and endemism. In a field work realized in an area of preserved Caatinga forest, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of a native species. These results of Vcmax measurements in Caatinga were compared with parameterization of models, revealing that Vcmax is not well adjusted in several DGVMs. Also, the values obtained in the Caatinga field experiments were very close to empirical values obtained in the Northern hemisphere (Austria). These ecophysiological measurements can contribute in understanding of this biome