A qualitative analysis of the congruency of Jungian psychological preferences identified by the Myers-Briggs Type Indicator (MBTI) and the human resource development role of instructor/facilitator

The purpose of this ethnographic study was to describe and explain the congruency of psychological preferences identified by the Myers-Briggs Type Indicator (MBTI) and the human resource development (HRD) role of instructor/facilitator. This investigation was conducted with 23 HRD professionals who worked in the Miami, Florida area as instructors/facilitators with adult learners in job-related contexts.^ The study was conducted using qualitative strategies of data collection and analysis. The research participants were selected through a purposive sampling strategy. Data collection strategies included: (a) administration and scoring of the MBTI, Form G, (b) open-ended and semi-structured interviews, (c) participant observations of the research subjects at their respective work sites and while conducting training sessions, (d) field notes, and (e) contact summary sheets to record field research encounters. Data analysis was conducted with the use of a computer program for qualitative analysis called FolioViews 3.1 for Windows. This included: (a) coding of transcribed interviews and field notes, (b) theme analysis, (c) memoing, and (d) cross-case analysis.^ The three major themes that emerged in relation to the congruency of psychological preferences and the role of instructor/facilitator were: (1) designing and preparing instruction/facilitation, (2) conducting training and managing group process, and (3) interpersonal relations and perspectives among instructors/facilitators.^ The first two themes were analyzed through the combination of the four Jungian personality functions. These combinations are: sensing-thinking (ST), sensing-feeling (SF), intuition-thinking (NT), and intuition-feeling (NF). The third theme was analyzed through the combination of the attitudes or energy focus and the judgment function. These combinations are: extraversion-thinking (ET), extraversion-feeling (EF), introversion-thinking (IT), and introversion-feeling (IF).^ A last area uncovered by this ethnographic study was the influence exerted by a training and development culture on the instructor/facilitator role. This professional culture is described and explained in terms of the shared values and expectations reported by the study respondents. ^

A qualitative analysis of the lived experience of nursing staff developers in the process of changing to a new educational model

The purpose of this study was to document and critically analyze the lived experience of selected nursing staff developers in the process of moving toward a new model for hospital nursing education. Eleven respondents were drawn from a nation-wide population of about two hundred individuals involved in nursing staff development. These subjects were responsible for the implementation of the Performance Based Development System (PBDS) in their institutions.^ A purposive, criterion-based sampling technique was used with respondents being selected according to size of hospital, primary responsibility for orchestration of the change, influence over budgetary factors and managerial responsibility for PBDS. Data were gathered by the researcher through both in-person and telephone interviews. A semi-structured interview guide, designed by the researcher was used, and respondents were encouraged to amplify on their recollections as desired. Audiotapes were transcribed and resulting computer files were analyzed using the program "Martin". Answers to interview questions were compiled and reported across cases. The data was then reviewed a second time and interpreted for emerging themes and patterns.^ Two types of verification were used in the study. Internal verification was done through interview transcript review and feedback by respondents. External verification was done through review and feedback on data analysis by readers who were experienced in management of staff development departments.^ All respondents were female, so Gilligan's concept of the "ethic of care" was examined as a decision making strategy. Three levels of caring which influenced decision making were found. They were caring: (a) for the organization, (b) for the employee, and (c) for the patient. The four existentials of the lived experience, relationality, corporeality, temporality and spatiality were also examined to reveal the everydayness of making change. ^

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is 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 for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Quantitative and qualitative comparison of 3.0 T and 1.5 T MR imaging of the liver in patients with diffuse parenchymal liver disease

Purpose: The purpose of our study was to compare signal characteristics and image qualities of MR imaging at 3.0 T and 1.5 T in patients with diffuse parenchymal liver disease. Materials and methods: 25 consecutive patients with diffuse parenchymal liver disease underwent abdominal MR imaging at both 3.0 T and 1.5 T within a 6-month interval. A retrospective study was conducted to obtain quantitative and qualitative data from both 3.0 T and 1.5 T MRI. Quantitative image analysis was performed by measuring the signal-to-noise ratios (SNRs) and the contrast-to-noise ratios (CNRs) by the Students t-test. Qualitative image analysis was assessed by grading each sequence on a 3- and 4-point scale, regarding the presence of artifacts and image quality, respectively. Statistical analysis consisted of the Wilcoxon signed-rank test. Results: the mean SNRs and CNRs of the liver parenchyma and the portal vein were significantly higher at 3.0 T than at 1.5 T on portal and equilibrium phases of volumetric interpolated breath-hold examination (VIBE) images (P < 0.05). The mean SNRs were significantly higher at 3.0 T than at 1.5 T on T1-weighted spoiled gradient echo (SGE) images (P < 0.05). However, there were no significantly differences on T2-weighted short-inversion-time inversion recovery (STIR) images. Overall image qualities of the 1.5 T noncontrast T1- and T2-weighted sequences were significantly better than 3.0 T (P < 0.01). In contrast, overall image quality of the 3.0 T post-gadolinium VIBE sequence was significantly better than 1.5 T (P< 0.01). Conclusions: MR imaging of post-gadolinium VIBE sequence at 3.0 T has quantitative and qualitative advantages of evaluating for diffuse parenchymal liver disease. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

A brief survey on online analysis of movement data

The increasing availability of mobility data and the awareness of its importance and value have been motivating many researchers to the development of models and tools for analyzing movement data. This paper presents a brief survey of significant research works about modeling, processing and visualization of data about moving objects. We identified some key research fields that will provide better features for online analysis of movement data. As result of the literature review, we suggest a generic multi-layer architecture for the development of an online analysis processing software tool, which will be used for the definition of the future work of our team.

Hierarchical cluster analysis of groups of individuals : application to business data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

On cluster analysis of complex and heterogeneous data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Miocene sediments from Foz da Fonte and Penedo sections (Lower Tagus basin): clay minerals and isotopic data

Eight depositional sequences (DS) delimited by regional disconformities had been recognized in the Miocene of Lisbon and Setúbal Peninsula areas. In the case of the western coast of the Setúbal Peninsula, outcrops consisting of Lower Burdigalian to Lower Tortonian sediments were studied. The stratigraphic zonography and the environmental considerations are mainly supported on data concerning to foraminifera, ostracoda, vertebrates and palynomorphs. The first mineralogical and geochemical data determined for Foz da Fonte, Penedo Sul and Penedo Norte sedimentary sequences are presented. These analytical data mainly correspond to the sediments' fine fractions. Mineralogical data are based on X-ray diffraction (XRD), carried out on both the less than 38 nm and 2 nm fractions. Qualitative and semi-quantitative determinations of clay and non-clay minerals were obtained for both fractions. The clay minerals assemblages complete the lithostratigraphic and paleoenvironmental data obtained by stratigraphic and palaeontological studies. Some palaeomagnetic and isotopic data are discussed and correlated with the mineralogical data. Multivariate data analysis (Principal Components Analysis) of the mineralogical data was carried out using both R-mode and Q-mode factor analysis.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Learning networks and moodle use in online courses: a social network analysis study

Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

A Process Analysis of Males and Females who Attended a Community Based Addiction Treatment Service: Towards an Expanded Paradigm

A process analysis was conducted in a community - based treatment programme for alcohol abuse. The aims of the study were: to evaluate assessment instruments and measures; to measure change following treatment; to monitor gender differences; to assess the importance of early and current relationships; and to evaluate the effects of therapists. Subjects (n=145, males 83/females 62) completed a semi-structured interview schedule, Severity of Alcohol Dependency Questionnaire (SADQ), Short Alcohol Dependence Data Questionnaire (SADD); General Health Questionnaire (GHQ 12), and Alcohol Problems Questionnaire (APQ). A further three non-standardised self-rated measures were devised by the author. Included was the opportunity to obtain qualitative data. Follow up data was collected at 3, 9 and 15 months following first assessment. The SADD, APQ and consumption measures using detailed drink diaries proved the most relevant assessment measures. Following treatment, there was significant reduction in clients' dependency levels at 3 months, maintained through 9 and 15 months. Key client-rated changes were progress in reducing consumption and alcohol problems leading to a better quality of life and health. Qualitative data augmented these quantitative results. Psychological and acquired cognitive behavioural skills emerged as the main reasons for positive change and the treatment programme was found to have played a significant role in their acquisition. It appears that addressing marital problems can lead to a reduction in alcohol dependency levels. Gender analysis showed that males and females were similar in demographic characteristics, alcohol history details and dependence levels. It was concluded that the differences found did not necessitate different treatment programmes for women. Early family relationships were more problematic for females. Therapist performance varied and that variance was reflected in their clients' outcomes.This resource was contributed by The National Documentation Centre on Drug Use.