Probabilistic principal component analysis

Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of parameters in a latent variable model closely related to factor analysis. We consider the properties of the associated likelihood function, giving an EM algorithm for estimating the principal subspace iteratively, and discuss the advantages conveyed by the definition of a probability density function for PCA.

Probabilistic principal component analysis

Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of parameters in a latent variable model closely related to factor analysis. We consider the properties of the associated likelihood function, giving an EM algorithm for estimating the principal subspace iteratively, and discuss the advantages conveyed by the definition of a probability density function for PCA.

Exchange fairness and employee performance:An examination of the relationship between organizational politics and procedural justice

Data obtained from a manufacturing firm and a newspaper firm in India were used to examine the relationship between organizational politics and procedural justice in three separate studies. Study 1 constructively replicated research on the distinctiveness of the two constructs. Confirmatory factor analyses in which data from the manufacturing firm served as the development sample and data from the newspaper firm served as the validation sample demonstrated the distinctiveness of organizational politics and procedural justice. Study 2 examined the antecedents of the two constructs using data from the manufacturing firm. Structural equation modeling (SEM) results revealed formalization and participation in decision making to be positively related to procedural justice but negatively related to organizational politics. Further, authority hierarchy and spatial distance were positively related to organizational politics but unrelated to procedural justice. Study 3 examined the consequences of the two constructs in terms of task and contextual performance using data from the newspaper firm. Results of SEM analysis revealed procedural justice but not organizational politics to be related to task performance and the contextual performance dimensions of interpersonal facilitation and job dedication. © 2004 Elsevier Inc. All rights reserved.

Organizational citizenship behavior and organizational commitment in Nepal

The present study examines the structure of organizational citizenship behavior (OCB) and its relation to organizational commitment in Nepal. Four-hundred and fifty employees of five Nepalese organizations filled out standardized questionnaires. Exploratory and confirmatory factor analyses revealed two factors of OCB, altruism and compliance, replicating Western models of extra-role behavior. Structural equation analysis showed a positive relation between affective and normative commitment on the one hand and both citizenship factors on the other. Continuance commitment was negatively related to compliance and unrelated to altruism. The findings thus confirmed the structure and usefulness of the concepts in an under-researched geographical area. Findings of the research are discussed within the Nepalese sociocultural context. © Blackwell Publishing Ltd with the Asian Association of Social Psychology and the Japanese Group Dynamics Association 2005.

Statnote 27: Principal components analysis (PCA)

In Statnotes 24 and 25, multiple linear regression, a statistical method that examines the relationship between a single dependent variable (Y) and two or more independent variables (X), was described. The principle objective of such an analysis was to determine which of the X variables had a significant influence on Y and to construct an equation that predicts Y from the X variables. ‘Principal components analysis’ (PCA) and ‘factor analysis’ (FA) are also methods of examining the relationships between different variables but they differ from multiple regression in that no distinction is made between the dependent and independent variables, all variables being essentially treated the same. Originally, PCA and FA were regarded as distinct methods but in recent times they have been combined into a single analysis, PCA often being the first stage of a FA. The basic objective of a PCA/FA is to examine the relationships between the variables or the ‘structure’ of the variables and to determine whether these relationships can be explained by a smaller number of ‘factors’. This statnote describes the use of PCA/FA in the analysis of the differences between the DNA profiles of different MRSA strains introduced in Statnote 26.

Understanding learning strategies in the workplace:a factor analytic investigation

The aim of this study was to validate a scale of learning strategies, as derived from the educational literature, in an organizational context. Participants were 628 call centre employees. Both exploratory and confirmatory factor analyses suggested that a six-factor structure most accurately represented the learning strategies examined. Specifically, three cognitive (extrinsic work reflection, intrinsic work reflection, reproduction) and three behavioural strategies (interpersonal help seeking, help seeking from written material, practical application) were found.

Statnote 28:Canonical Variate Analysis (CVA)

The pattern of correlation between two sets of variables can be tested using canonical variate analysis (CVA). CVA, like principal components analysis (PCA) and factor analysis (FA) (Statnote 27, Hilton & Armstrong, 2011b), is a multivariate analysis Essentially, as in PCA/FA, the objective is to determine whether the correlations between two sets of variables can be explained by a smaller number of ‘axes of correlation’ or ‘canonical roots’.

A survey based analysis of IT adoption and 3PLs' performance

Purpose: In today's competitive scenario, effective supply chain management is increasingly dependent on third-party logistics (3PL) companies' capabilities and performance. The dissemination of information technology (IT) has contributed to change the supply chain role of 3PL companies and IT is considered an important element influencing the performance of modern logistics companies. Therefore, the purpose of this paper is to explore the relationship between IT and 3PLs' performance, assuming that logistics capabilities play a mediating role in this relationship. Design/methodology/approach: Empirical evidence based on a questionnaire survey conducted on a sample of logistics service companies operating in the Italian market was used to test a conceptual resource-based view (RBV) framework linking IT adoption, logistics capabilities and firm performance. Factor analysis and ordinary least square (OLS) regression analysis have been used to test hypotheses. The focus of the paper is multidisciplinary in nature; management of information systems, strategy, logistics and supply chain management approaches have been combined in the analysis. Findings: The results indicate strong relationships among data gathering technologies, transactional capabilities and firm performance, in terms of both efficiency and effectiveness. Moreover, a positive correlation between enterprise information technologies and 3PL financial performance has been found. Originality/value: The paper successfully uses the concept of logistics capabilities as mediating factor between IT adoption and firm performance. Objective measures have been proposed for IT adoption and logistics capabilities. Direct and indirect relationships among variables have been successfully tested. © Emerald Group Publishing Limited.

Determinants of resource development strategies in nonprofit organizations: An analysis of children, youth and family services

This study is an exploratory analysis of an operational measure for resource development strategies, and an exploratory analysis of internal organizational contingencies influencing choices of these strategies in charitable nonprofit organizations. The study provides conceptual guidance for advancing understanding about resource development in the nonprofit sector. The statistical findings are, however, inconclusive without further rigorous examination. A three category typology based on organization technology is initially presented to define the strategies. Three dimensions of internal organizational contingencies explored represent organization identity, professional staff, and boards of directors. Based on relevant literature and key informant interviews, an original survey was administered by mail to a national sample of nonprofit organizations. The survey collected data on indicators of the proposed strategy types and selected contingencies. Factor analysis extracted two of the initial categories in the typology. The Building Resource Development Infrastructure Strategy encompasses information technology, personnel, legal structures, and policies facilitating fund development. The Building Resource Development Infrastructure Strategy encompasses the mission, service niche, and type of service delivery forming the basis for seeking financial support. Linear regressions with each strategy type as the dependent variable identified distinct and common contingencies which may partly explain choices of strategies. Discriminant analysis suggests the potential predictive accuracy of the contingencies. Follow-up case studies with survey respondents provide additional criteria for operationalizing future measures of resource development strategies, and support and expand the analysis on contingencies. The typology offers a beginning framework for defining alternative approaches to resource development, and for exploring organization capacity specific to each approach. Contingencies that may be integral components of organization capacity are funding, leadership frame, background and experience, staff and volunteer effort, board member support, and relationships in the external environment. Based on these findings, management questions are offered for nonprofit organization stakeholders to consider in planning for resource development. Lessons learned in designing and conducting this study are also provided to enhance future related research. ^

Fiscal and organizational determinants of transportation outcomes: A quantitative and qualitative analysis of sustainability factors

Federal transportation legislation in effect since 1991 was examined to determine outcomes in two areas: (1) The effect of organizational and fiscal structures on the implementation of multimodal transportation infrastructure, and (2) The effect of multimodal transportation infrastructure on sustainability. Triangulation of methods was employed through qualitative analysis (including key informant interviews, focus groups and case studies), as well as quantitative analysis (including one-sample t-tests, regression analysis and factor analysis). ^ Four hypotheses were directly tested: (1) Regions with consolidated government structures will build more multimodal transportation miles: The results of the qualitative analysis do not lend support while the results of the quantitative findings support this hypothesis, possibly due to differences in the definitions of agencies/jurisdictions between the two methods. (2) Regions in which more locally dedicated or flexed funding is applied to the transportation system will build a greater number of multimodal transportation miles: Both quantitative and qualitative research clearly support this hypothesis. (3) Cooperation and coordination, or, conversely, competition will determine the number of multimodal transportation miles: Participants tended to agree that cooperation, coordination and leadership are imperative to achieving transportation goals and objectives, including targeted multimodal miles, but also stressed the importance of political and financial elements in determining what ultimately will be funded and implemented. (4) The modal outcomes of transportation systems will affect the overall health of a region in terms of sustainability/quality of life indicators: Both the qualitative and the quantitative analyses provide evidence that they do. ^ This study finds that federal legislation has had an effect on the modal outcomes of transportation infrastructure and that there are links between these modal outcomes and the sustainability of a region. It is recommended that agencies further consider consolidation and strengthen cooperation efforts and that fiscal regulations are modified to reflect the problems cited in qualitative analysis. Limitations of this legislation especially include the inability to measure sustainability; several measures are recommended. ^

Gaussian Process Kernels for Cross-Spectrum Analysis in Electrophysiological Time Series

Multi-output Gaussian processes provide a convenient framework for multi-task problems. An illustrative and motivating example of a multi-task problem is multi-region electrophysiological time-series data, where experimentalists are interested in both power and phase coherence between channels. Recently, the spectral mixture (SM) kernel was proposed to model the spectral density of a single task in a Gaussian process framework. This work develops a novel covariance kernel for multiple outputs, called the cross-spectral mixture (CSM) kernel. This new, flexible kernel represents both the power and phase relationship between multiple observation channels. The expressive capabilities of the CSM kernel are demonstrated through implementation of 1) a Bayesian hidden Markov model, where the emission distribution is a multi-output Gaussian process with a CSM covariance kernel, and 2) a Gaussian process factor analysis model, where factor scores represent the utilization of cross-spectral neural circuits. Results are presented for measured multi-region electrophysiological data.

The experience of teaching statistics to non-specialist students in Saudi universities

Undoubtedly, statistics has become one of the most important subjects in the modern world, where its applications are ubiquitous. The importance of statistics is not limited to statisticians, but also impacts upon non-statisticians who have to use statistics within their own disciplines. Several studies have indicated that most of the academic departments around the world have realized the importance of statistics to non-specialist students. Therefore, the number of students enrolled in statistics courses has vastly increased, coming from a variety of disciplines. Consequently, research within the scope of statistics education has been able to develop throughout the last few years. One important issue is how statistics is best taught to, and learned by, non-specialist students. This issue is controlled by several factors that affect the learning and teaching of statistics to non-specialist students, such as the use of technology, the role of the English language (especially for those whose first language is not English), the effectiveness of statistics teachers and their approach towards teaching statistics courses, students’ motivation to learn statistics and the relevance of statistics courses to the main subjects of non-specialist students. Several studies, focused on aspects of learning and teaching statistics, have been conducted in different countries around the world, particularly in Western countries. Conversely, the situation in Arab countries, especially in Saudi Arabia, is different; here, there is very little research in this scope, and what there is does not meet the needs of those countries towards the development of learning and teaching statistics to non-specialist students. This research was instituted in order to develop the field of statistics education. The purpose of this mixed methods study was to generate new insights into this subject by investigating how statistics courses are currently taught to non-specialist students in Saudi universities. Hence, this study will contribute towards filling the knowledge gap that exists in Saudi Arabia. This study used multiple data collection approaches, including questionnaire surveys from 1053 non-specialist students who had completed at least one statistics course in different colleges of the universities in Saudi Arabia. These surveys were followed up with qualitative data collected via semi-structured interviews with 16 teachers of statistics from colleges within all six universities where statistics is taught to non-specialist students in Saudi Arabia’s Eastern Region. The data from questionnaires included several types, so different techniques were used in analysis. Descriptive statistics were used to identify the demographic characteristics of the participants. The chi-square test was used to determine associations between variables. Based on the main issues that are raised from literature review, the questions (items scales) were grouped and five key groups of questions were obtained which are: 1) Effectiveness of Teachers; 2) English Language; 3) Relevance of Course; 4) Student Engagement; 5) Using Technology. Exploratory data analysis was used to explore these issues in more detail. Furthermore, with the existence of clustering in the data (students within departments within colleges, within universities), multilevel generalized linear models for dichotomous analysis have been used to clarify the effects of clustering at those levels. Factor analysis was conducted confirming the dimension reduction of variables (items scales). The data from teachers’ interviews were analysed on an individual basis. The responses were assigned to one of the eight themes that emerged from within the data: 1) the lack of students’ motivation to learn statistics; 2) students' participation; 3) students’ assessment; 4) the effective use of technology; 5) the level of previous mathematical and statistical skills of non-specialist students; 6) the English language ability of non-specialist students; 7) the need for extra time for teaching and learning statistics; and 8) the role of administrators. All the data from students and teachers indicated that the situation of learning and teaching statistics to non-specialist students in Saudi universities needs to be improved in order to meet the needs of those students. The findings of this study suggested a weakness in the use of statistical software applications in these courses. This study showed that there is lack of application of technology such as statistical software programs in these courses, which would allow non-specialist students to consolidate their knowledge. The results also indicated that English language is considered one of the main challenges in learning and teaching statistics, particularly in institutions where English is not used as the main language. Moreover, the weakness of mathematical skills of students is considered another major challenge. Additionally, the results indicated that there was a need to tailor statistics courses to the needs of non-specialist students based on their main subjects. The findings indicate that statistics teachers need to choose appropriate methods when teaching statistics courses.

Analysis of the failure of cracked biscuits

Cracks or checks in biscuits weaken the material and cause the product to break at low load levels that are perceived as injurious to product quality. In this work, the structural response of circular digestive biscuits, with diameter 72 mm and thickness 7.2 mm, simply supported around the circumference and loaded by a central concentrated force was investigated by experiment and theory. Tests were conducted to quantify the distribution in breakage strength for structurally sound biscuits, biscuits with natural checks and biscuits with a single known part-through crack. For sound biscuits the breakage force is Normally distributed with a mean of 12.5 N and standard deviation of 1.2 N. For biscuits with checks, the corresponding statistics are 9.6 N ± 2.62 N respectively. The presence of a crack weakens the biscuit and strength, as measured by breakage force falls almost linearly with crack length and crack depth. The orientation of the crack, whether radial or tangential, and its location (i.e. position of the crack mid-point on the biscuit surface) are also important. Deep, radial, cracks located close to the biscuit centre can reduce the strength by up to 50%. Two separate failure criteria were examined for sound and cracked biscuits respectively. The results from these tests were in good accord with theory. For a biscuit without defects, breakage occurred when maximum biscuit stress reached or exceeded the failure stress of 420 kPa. For a biscuit with cracks, breakage occurred as above or alternatively when its critical stress intensity factor of 18 kPam0.5 was reached.

An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data

Min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA) are complementary techniques for analysing short (> 15-25 y), non-stationary, multivariate data sets. We illustrate the two techniques using catch rate (cpue) time-series (1982-2001) for 17 species caught during trawl surveys off Mauritania, with the NAO index, an upwelling index, sea surface temperature, and an index of fishing effort as explanatory variables. Both techniques gave coherent results, the most important common trend being a decrease in cpue during the latter half of the time-series, and the next important being an increase during the first half. A DFA model with SST and UPW as explanatory variables and two common trends gave good fits to most of the cpue time-series. (c) 2004 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

Congruencia entre los valores personales y organizacionales y su influencia con el engagement en el trabajo : estudio de caso en una organización del sector salud

La capacidad de gestión del personal se ha convertido en un imperativo para las organizaciones modernas. Por tanto se vienen introduciendo temas como la administración en valores y el engagement de los trabajadores. Sin embargo, la relación entre estos dos aún no ha sido estudiada. El presente estudio tiene como objetivo analizar el efecto que tiene el grado de articulación y reconocimiento de los valores organizacionales y personales y organizacionales sobre los niveles de engagement de los empleados. Para esta investigación se utilizó una muestra constituida por 54 trabajadores de una organización del sector salud de la ciudad de Bogotá a quienes les fueron aplicadas dos escalas: el Inventario para Medir la Articulación entre la Persona y la Organización (Inventario APO) y Utrech Work Engagement Scale (UWES). Como principal resultado se obtuvo que de las tres dimensiones consideradas predictoras del engagement, solamente el reconocimiento de los valores organizacionales tuvo un efecto estadísticamente significativo.