Impact of incorrect assumptions on the covariance structure of random effects and/or residuals in nonlinear mixed models for repeated measures data

In this paper we analyse, using Monte Carlo simulation, the possible consequences of incorrect assumptions on the true structure of the random effects covariance matrix and the true correlation pattern of residuals, over the performance of an estimation method for nonlinear mixed models. The procedure under study is the well known linearization method due to Lindstrom and Bates (1990), implemented in the nlme library of S-Plus and R. Its performance is studied in terms of bias, mean square error (MSE), and true coverage of the associated asymptotic confidence intervals. Ignoring other criteria like the convenience of avoiding over parameterised models, it seems worst to erroneously assume some structure than do not assume any structure when this would be adequate.

Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA)

Background: MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.Results: Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.Conclusion: Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.

Social reciprocity measures based on dyadic discrepancies: Methodological review and software development

This paper examines statistical analysis of social reciprocity at group, dyadic, and individual levels. Given that testing statistical hypotheses regarding social reciprocity can be also of interest, a statistical procedure based on Monte Carlo sampling has been developed and implemented in R in order to allow social researchers to describe groups and make statistical decisions.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Erupted odontomas: a report of three cases and review of the literature

Introduction: Odontomas are benign odontogenic tumors composed of enamel, dentine, cement and pulp tissue. They are usually clinically asymptomatic, but often associated with tooth eruption disturbances. In exceptional cases the odontoma erupts into the mouth. The present study reports three cases of odontomas erupted into the oral cavity and reviews the literature. Clinical cases: The first case was an 11-year-old girl with impacted 4.6 associated to a radiopaque mass measuring about 2 cm in diameter. The histological diagnosis was complex odontoma. A clinical and radiological follow-up of 4.6 was carried out until its spontaneous eruption. The second case was a 26-year-old male presenting a hard, yellowish-brown mass located distal to the upper left second molar. Computed tomography confi rmed the presence of a radiopaque lesion, and the histopathological study confirmed a complex odontoma. The third patient was a 27-year-old male reporting tongue irritation due to tooth eruption in the inferior lingual region. A periapical radiograph revealed a mixed radiopaque lesion associated to impacted 3.2. The histological report in this case indicated a compound odontoma. Discussion: Odontomas erupting into the oral cavity are rare. The first case was published in 1980, and since then only 17 cases have been reported in the literature. Eight of the 17 cases were complex odontomas; the rest were compound odontomas. Pain, swelling and infection were the most common symptoms, and 13 cases presented an impacted tooth associated with the lesion

Pilomatrixoma. Review of 205 cases

Aims: To determine the incidence and clinical features of patients diagnosed with pilomatrixoma. Patients and Method: A retrospective analysis was made of 205 cases of pilomatrixoma diagnosed according to clinical and histological criteria, with an evaluation of the incidence, patient age at presentation, gender, lesion location and size, single or multiple presentation, differential diagnosis, histopathological and clinical findings and relapses. Results: Pilomatrixoma was seen to account for 1.04% of all benign skin lesions. It tended to present in pediatric patients- almost 50% corresponding to individuals under 20 years of age- with a slight male predilection (107/98). Approximately 75% of all cases presented as single lesions measuring less than 15 mm in diameter. Multiple presentations were seen in 2.43% of cases. The most frequent locations were the head and orofacial zones (particularly the parotid region), with over 50% of all cases, followed by the upper (23.9%) and lower limbs (12.7%). Only one relapse was documented following simple lesion excision. Conclusions: The frequency of pilomatrixomas was 1.04% of all benign skin lesions- the lesions being predominantly located in the maxillofacial area. Due to the benign features of this disorder, simple removal of the lesion is considered to be the treatment of choice, and is associated with a very low relapse rate.

Case-Crossover Analysis of Air Pollution Health Effects: A Systematic Review of Methodology and Application

Case-crossover is one of the most used designs for analyzing the health-related effects of air pollution. Nevertheless, no one has reviewed its application and methodology in this context. Objective: We conducted a systematic review of case-crossover (CCO) designs used to study the relationship between air pollution and morbidity and mortality, from the standpoint of methodology and application.Data sources and extraction: A search was made of the MEDLINE and EMBASE databases.Reports were classified as methodologic or applied. From the latter, the following information was extracted: author, study location, year, type of population (general or patients), dependent variable(s), independent variable(s), type of CCO design, and whether effect modification was analyzed for variables at the individual level. Data synthesis: The review covered 105 reports that fulfilled the inclusion criteria. Of these, 24 addressed methodological aspects, and the remainder involved the design’s application. In the methodological reports, the designs that yielded the best results in simulation were symmetric bidirectional CCO and time-stratified CCO. Furthermore, we observed an increase across time in the use of certain CCO designs, mainly symmetric bidirectional and time-stratified CCO. The dependent variables most frequently analyzed were those relating to hospital morbidity; the pollutants most often studied were those linked to particulate matter. Among the CCO-application reports, 13.6% studied effect modification for variables at the individual level.Conclusions: The use of CCO designs has undergone considerable growth; the most widely used designs were those that yielded better results in simulation studies: symmetric bidirectional and time-stratified CCO. However, the advantages of CCO as a method of analysis of variables at the individual level are put to little use

Setting priorities in clinical and health services research: Properties of an adapted and updated method

Objectives: The objectives of this study is to review the set of criteria of the Institute of Medicine (IOM) for priority-setting in research with addition of new criteria if necessary, and to develop and evaluate the reliability and validity of the final priority score. Methods: Based on the evaluation of 199 research topics, forty-five experts identified additional criteria for priority-setting, rated their relevance, and ranked and weighted them in a three-round modified Delphi technique. A final priority score was developed and evaluated. Internal consistency, test–retest and inter-rater reliability were assessed. Correlation with experts’ overall qualitative topic ratings were assessed as an approximation to validity. Results: All seven original IOM criteria were considered relevant and two new criteria were added (“potential for translation into practice”, and “need for knowledge”). Final ranks and relative weights differed from those of the original IOM criteria: “research impact on health outcomes” was considered the most important criterion (4.23), as opposed to “burden of disease” (3.92). Cronbach’s alpha (0.75) and test–retest stability (interclass correlation coefficient = 0.66) for the final set of criteria were acceptable. The area under the receiver operating characteristic curve for overall assessment of priority was 0.66. Conclusions: A reliable instrument for prioritizing topics in clinical and health services research has been developed. Further evaluation of its validity and impact on selecting research topics is required

The use of mixed methods research in the behavioral sciences field

Mixed methods research involves the combined use of quantitative and qualitative methods in the same research study, and it is becoming increasingly important in several scientific areas. The aim of this paper is to review and compare through a mixed methods multiple-case study the application of this methodology in three reputable behavioural science journals: the Journal of Organizational Behavior, Addictive Behaviors and Psicothema. A quantitative analysis was carried out to review all the papers published in these journals during the period 2003-2008 and classify them into two blocks: theoretical and empirical, with the latter being further subdivided into three subtypes (quantitative, qualitative and mixed). A qualitative analysis determined the main characteristics of the mixed methods studies identified, in order to describe in more detail the ways in which the two methods are combined based on their purpose, priority, implementation and research design. From the journals selected, a total of 1.958 articles were analysed, the majority of which corresponded to empirical studies, with only a small number referring to research that used mixed methods. Nonetheless, mixed methods research does appear in all the behavioural science journals studied within the period selected, showing a range of designs, where the sequential equal weight mixed methods research design seems to stand out.

The use of mixed methods research in interdisciplinary educational journals

Mixed methods research is becoming increasingly important in several scientific areas. The analysis of prevalence rates is a new line of research that has emerged in mixed methods research, and this methodological approach has only been applied carefully in a handful of journals. The purpose of this article was to analyse the prevalence of mixed methods research in interdisciplinary educational journals. Moreover, the main characteristics of the mixed methods articles identified were examined. This study used a mixed methods approach to analyse these aspects. Specifically, a partially mixed sequential equal status multiple-case study design was applied with a development mixed methods purpose. Three educational journals in different disciplines were reviewed from 2005 to 2010 (Academy of Management Learning and Education, Educational Psychology Review, Journal of the Learning Sciences). The findings show differences among the journals in the prevalence rates and characteristics of the mixed methods studies