A Gaussian pseudolikelihood approach for quantile regression with repeated measurements

To enhance the efficiency of regression parameter estimation by modeling the correlation structure of correlated binary error terms in quantile regression with repeated measurements, we propose a Gaussian pseudolikelihood approach for estimating correlation parameters and selecting the most appropriate working correlation matrix simultaneously. The induced smoothing method is applied to estimate the covariance of the regression parameter estimates, which can bypass density estimation of the errors. Extensive numerical studies indicate that the proposed method performs well in selecting an accurate correlation structure and improving regression parameter estimation efficiency. The proposed method is further illustrated by analyzing a dental dataset.

Approximation of Bayesian predictive p-values with regression ABC

In the Bayesian framework a standard approach to model criticism is to compare some function of the observed data to a reference predictive distribution. The result of the comparison can be summarized in the form of a p-value, and it's well known that computation of some kinds of Bayesian predictive p-values can be challenging. The use of regression adjustment approximate Bayesian computation (ABC) methods is explored for this task. Two problems are considered. The first is the calibration of posterior predictive p-values so that they are uniformly distributed under some reference distribution for the data. Computation is difficult because the calibration process requires repeated approximation of the posterior for different data sets under the reference distribution. The second problem considered is approximation of distributions of prior predictive p-values for the purpose of choosing weakly informative priors in the case where the model checking statistic is expensive to compute. Here the computation is difficult because of the need to repeatedly sample from a prior predictive distribution for different values of a prior hyperparameter. In both these problems we argue that high accuracy in the computations is not required, which makes fast approximations such as regression adjustment ABC very useful. We illustrate our methods with several samples.

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

A fast semi-implicit difference method for a nonlinear two-sided space-fractional diffusion equation with variable diffusivity coefficients

In this paper, we derive a new nonlinear two-sided space-fractional diffusion equation with variable coefficients from the fractional Fick’s law. A semi-implicit difference method (SIDM) for this equation is proposed. The stability and convergence of the SIDM are discussed. For the implementation, we develop a fast accurate iterative method for the SIDM by decomposing the dense coefficient matrix into a combination of Toeplitz-like matrices. This fast iterative method significantly reduces the storage requirement of O(n2)O(n2) and computational cost of O(n3)O(n3) down to n and O(nlogn)O(nlogn), where n is the number of grid points. The method retains the same accuracy as the underlying SIDM solved with Gaussian elimination. Finally, some numerical results are shown to verify the accuracy and efficiency of the new method.

Rejected! The harmful effects of workgroup mistreatment and the moderating role of organisational norms

This program of research investigated the harmful effects of mistreatment by the workgroup, and the role of perceived rejection as a critical mediator linking mistreatment and outcomes. This research program had three primary purposes. First, the research aimed to examine the important role of workgroup mistreatment as an independent predictor of negative outcomes, over and above the influence of supervisor mistreatment. Second, the research aimed to examine the effect of perceived rejection as an explanatory variable linking workgroup mistreatment and outcomes. Finally, the moderating effect of organizational norms on the relationship between workgroup mistreatment and perceived rejection was examined. The relationships of interest were examined over four studies, using multiple methods of data collection, across part-time and full-time working samples. In Study 1 (Chapter 2), the independent role of workgroup mistreatment and the mediating role of perceived rejection were examined. One hundred and forty two part-time working participants took part in the study. The participants completed a questionnaire on workplace behaviors in their organizations. The results of hierarchical regression analyses revealed a strong harmful effect of workgroup mistreatment, independent of mistreatment by the supervisor. In addition, the results showed that perceived rejection fully mediated the relationship between workgroup mistreatment and depression and organizational based self esteem. The study highlighted that perceived rejection acts as a key underlying psychological mechanism involved in the effect of workgroup mistreatment. This study has been published in the Journal of Occupational Health Psychology. Study 2 and Study 3 were presented as one paper in Chapter 3. The aims of these two studies was to explore the effects of workgroup mistreatment on a wider range of individual and organizational level outcomes, and to provide further evidence of the mediating role of perceived rejection as observed in Study 1. The results from both studies demonstrated that workgroup mistreatment had a significant and independent role in predicting negative individual and organizational level outcomes, providing support for the findings of Study 1. In the first study, 189 participants received scenarios manipulating workgroup mistreatment and supervisor mistreatment. The results of hierarchical regression analyses revealed that workgroup mistreatment harmfully affected participants, over and above that of the supervisor. The results also demonstrated that perceived rejection mediated the positive relationships between workgroup mistreatment and depression and organizational deviance, and also the negative relationships between workgroup mistreatment and organizational based self esteem and organizational citizenship behaviors. The second study included an additional aim, to examine the moderating role of supportive organizational norms. Two hundred and twenty nine participants read scenarios that manipulated workgroup mistreatment, supervisor mistreatment and organizational norms. The results of hierarchical regression analyses revealed the significant harmful effects of workgroup mistreatment, over and above the influence of supervisor mistreatment. The results also revealed the mediating role of perceived rejection. The direct effect of positive organizational norms also emerged, consistent with previous research. In addition, the result revealed that employees who experienced supportive organizational norms were more likely to reconcile with their workgroup members after experiencing mistreatment compared to employees who experienced hostile organizational norms. Finally, an unexpected pattern on the key affective variables of depression and organizational based self esteem emerged, such that mistreatment led to more negative outcomes in the supportive norms condition than in the hostile condition, where employees appeared to be desensitized. This paper is currently under review at the Journal of Applied Social Psychology. In Study 4 (Chapter 4), the overall model of workplace mistreatment was tested on a sample of full-time workers in an applied setting. One hundred and seventy two adults took part in the study. Participants were required to evaluate their workplace regarding mistreatment and organizational norms and to report their own psychological, behavioral and organizational outcomes. The results revealed that workgroup mistreatment was associated with increased depression, stress and avoidance, over and above supervisor mistreatment. In addition, the results revealed that perceived rejection acted as an explanatory variable linking workgroup mistreatment to a number of outcomes. Furthermore, the moderating role of hostile organizational norms emerged on depression, stress, reconciliation and avoidance. This paper is currently under review at the Journal of Occupational Health Psychology. Overall, the four studies provided empirical support for the majority of the hypotheses. The effects were demonstrated for a range of psychological, behavioral, and organizational level outcomes, using multiple methods of data collection, across part-time and full-time workers. At the conclusion of the thesis (Chapter 5), an overall summary is provided of the findings across all four studies, practical and theoretical implications and research directions.

Variable phenotype in 16p duplication within a family

Background More individuals are now being identified with very rare genetic syndromes. We present a family with an inherited duplication of 16p11.2 to 16q12.1 in ring formation. Three of the four children, (aged 15 months to 10 years), mother, uncle, and grandmother are affected. Our aim was to provide preliminary evidence of possible phenotypic patterns of learning and behaviour associated with this chromosome anomaly. Method Psychometric assessments were undertaken with all four children. The mother and uncle also agreed to participate in the study. Measures of development (Bayley or Mullen), intellectual ability (WISC-IV or WAIS-III), academic achievement (WIAT-II), adaptive behaviour (Vinelands), and other relevant aspects of functioning (e.g., Children’s Memory Scale) were administered. Results. The first-born child is the only one who is unaffected. Her intellectual ability was assessed as being within the superior range. The second child experienced early difficulties with speech and motor skills. Although his intelligence is average, he has learning difficulties and significant auditory memory problems. The third child’s speech and motor milestones were markedly delayed. He has a complex medical history that includes a vitamin B12 deficiency. On the Mullen Scales at age 4 his scores ranged from average to very low. The development of the youngest child (aged 15 months), who also had a B12 deficiency but was treated early, was assessed as being within typical limits. Conclusions There is considerable developmental variability among the three children with this inherited 16p duplication. We discuss the intriguing similarities and differences, considering common features that may reflect phenotypic patterns and speculating about possible explanations for the variable presentations.

Numerical treatment of a two-dimensional variable-order fractional nonlinear reaction-diffusion model

A two-dimensional variable-order fractional nonlinear reaction-diffusion model is considered. A second-order spatial accurate semi-implicit alternating direction method for a two-dimensional variable-order fractional nonlinear reaction-diffusion model is proposed. Stability and convergence of the semi-implicit alternating direct method are established. Finally, some numerical examples are given to support our theoretical analysis. These numerical techniques can be used to simulate a two-dimensional variable order fractional FitzHugh-Nagumo model in a rectangular domain. This type of model can be used to describe how electrical currents flow through the heart, controlling its contractions, and are used to ascertain the effects of certain drugs designed to treat arrhythmia.

The influence of family history of hypertension on disease prevalence and associated metabolic risk factors among Sri Lankan adults

Background Hypertension is a major contributor to the global non-communicable disease burden. Family history is an important non-modifiable risk factor for hypertension. The present study aims to describe the influence of family history (FH) on hypertension prevalence and associated metabolic risk factors in a large cohort of South Asian adults, from a nationally representative sample from Sri Lanka. Methods A cross-sectional survey among 5,000 Sri Lankan adults, evaluating FH at the levels of parents, grandparents, siblings and children. A binary logistic regression analysis was performed in all patients with ‘presence of hypertension’ as dichotomous dependent variable and using family history in parents, grandparents, siblings and children as binary independent variables. The adjusted odds ratio controlling for confounders (age, gender, body mass index, diabetes, hyperlipidemia and physical activity) are presented below. Results In all adults the prevalence of hypertension was significantly higher in patients with a FH (29.3 %, n = 572/1951) than those without (24.4 %, n = 616/2530) (p < 0.001). Presence of a FH significantly increased the risk of hypertension (OR:1.29; 95 % CI:1.13-1.47), obesity (OR:1.36; 95 % CI: 1.27–1.45), central obesity (OR:1.30; 95 % CI 1.22–1.40) and metabolic syndrome (OR:1.19; 95 % CI: 1.08–1.30). In all adults presence of family history in parents (OR:1.28; 95 % CI: 1.12–1.48), grandparents (OR:1.34; 95 % CI: 1.20–1.50) and siblings (OR:1.27; 95 % CI: 1.21–1.33) all were associated with significantly increased risk of developing hypertension. Conclusions Our results show that the prevalence of hypertension was significantly higher in those with a FH of hypertension. FH of hypertension was also associated with the prevalence of obesity, central obesity and metabolic syndrome. Individuals with a FH of hypertension form an easily identifiable group who may benefit from targeted interventions.

Using decision trees to understand structure in missing data

Objectives Demonstrate the application of decision trees – classification and regression trees (CARTs), and their cousins, boosted regression trees (BRTs) – to understand structure in missing data. Setting Data taken from employees at three different industry sites in Australia. Participants 7915 observations were included. Materials and Methods The approach was evaluated using an occupational health dataset comprising results of questionnaires, medical tests, and environmental monitoring. Statistical methods included standard statistical tests and the ‘rpart’ and ‘gbm’ packages for CART and BRT analyses, respectively, from the statistical software ‘R’. A simulation study was conducted to explore the capability of decision tree models in describing data with missingness artificially introduced. Results CART and BRT models were effective in highlighting a missingness structure in the data, related to the Type of data (medical or environmental), the site in which it was collected, the number of visits and the presence of extreme values. The simulation study revealed that CART models were able to identify variables and values responsible for inducing missingness. There was greater variation in variable importance for unstructured compared to structured missingness. Discussion Both CART and BRT models were effective in describing structural missingness in data. CART models may be preferred over BRT models for exploratory analysis of missing data, and selecting variables important for predicting missingness. BRT models can show how values of other variables influence missingness, which may prove useful for researchers. Conclusion Researchers are encouraged to use CART and BRT models to explore and understand missing data.

Contribución de la fuerza y el dolor en la función del paciente con artrosis trapecio metacarpiana. Estudio transversal

Objetivo Establecer una posible relación entre la fuerza (Jamar), el dolor (EVA) y la capacidad funcional referida por el paciente (DASH) determinando en qué grado influyen unas en otras. Estudio observacional transversal analítico. Participantes Muestra de 72 pacientes que presentaban una artrosis trapecio metacarpiana grado 2-3 de Eaton. Los pacientes fueron reclutados cuando acudían a la Unidad de Cirugía de mano. Método Se realizaron mediciones de fuerza de agarre, pinza, valoración del dolor y funcionalidad, y se establecieron las correlaciones entre cada una de ellas. Resultados El modelo más significativo para la función (R2 =0.83) incluye la variable dolor y la fuerza. Pero es la fuerza punta contra punta la que presenta una mayor correlación con el cuestionario DASH (B-estandarizado: –57). Respecto al dolor, influye en todas las mediciones de fuerza realizadas con el dinamómetro, siendo también la fuerza de la pinza punta contra punta la que presenta una mayor correlación. Conclusiones Los hallazgos corroboran que existe una correlación significativa entre la función referida por el paciente y variables que podemos medir en consulta, como la fuerza del puño y la pinza. Pero también esta correlación es significativa entre las variables función y dolor entre sí, pero es la pinza punta contra punta la que presenta una mayor asociación con el cuestionario DASH. Abstract in English Objective To assess the relationship between muscle strength (Jama), and pain (VAS) levels with hand function (DASH) in patients with trapeziometarcapal osteoarthritis. Cross-sectional study. Participants Sample of 72 patients with osteoarthritis stage 2-3 (Eaton) and trapeziometacarpal osteoarthritis. Patients were recruited when they came to the Hand Surgery Unit. Method Grip strength, pinch, pain and hand function were measured, and correlation and regression coefficients between them were obtained. Results For function, the most significant model (R2 = 0.83) included pain and strength. But it is tip to tip pinch force which has a stronger relationship with DASH (Standardized B: –57) questionnaire. Pain also influenced strength measured with the dynamometer but it was tip to tip pinch force that was the most affected. Conclusions Findings confirm that there is a significant correlation between function referred by the patient and variables that can be measured in the clinic such as grip strength and pinch. The correlation between pain intensity and function was also significant, but tip to tip pinch strength had the greatest impact on the function.

Electromyography and sonomyography analysis of the tibialis anterior: a cross sectional study

Background Foot dorsiflexion plays an essential role in both controlling balance and human gait. Electromyography (EMG) and sonomyography (SMG) can provide information on several aspects of muscle function. The aim was to establish the relationship between the EMG and SMG variables during isotonic contractions of foot dorsiflexors. Methods Twenty-seven healthy young adults performed the foot dorsiflexion test on a device designed ad hoc. EMG variables were maximum peak and area under the curve. Muscular architecture variables were muscle thickness and pennation angle. Descriptive statistical analysis, inferential analysis and a multivariate linear regression model were carried out. The confidence level was established with a statistically significant p-value of less than 0.05. Results The correlation between EMG variables and SMG variables was r = 0.462 (p < 0.05). The linear regression model to the dependent variable “peak normalized tibialis anterior (TA)” from the independent variables “pennation angle and thickness”, was significant (p = 0.002) with an explained variance of R2 = 0.693 and SEE = 0.16. Conclusions There is a significant relationship and degree of contribution between EMG and SMG variables during isotonic contractions of the TA muscle. Our results suggest that EMG and SMG can be feasible tools for monitoring and assessment of foot dorsiflexors. TA muscle parameterization and assessment is relevant in order to know that increased strength accelerates the recovery of lower limb injuries.