Previous research has individually assessed parallel analysis and minimum average partial for factor retention in exploratory factor analysis using ordinal variables. The current study is a comprehensive simulation study including the manipulation of eight conditions (type of correlation matrix, sample size, number of variables per factor, number of factors, factor correlation, skewness, factor loadings, and number of response categories), and three types of retention methods (minimum average partial, parallel analysis, and empirical Kaiser criterion) resulting in a 2 × 2 × 2 × 2 × 2 × 3 × 3 × 4 × 5 design that totals to 5,760 condition combinations tested over 1,000 replications each. Results show that each retention method performed worse when utilizing polychoric correlation matrices. Moreover, minimum average partials are quite sensitive to factor loadings and overall perform poorly compared to parallel analysis and empirical Kaiser criterion. Empirical Kaiser criterion performed almost identical to parallel analysis in normally distributed data; however, performed much worse under highly skewed conditions. Based on these findings, it is recommended to use parallel analysis utilizing principal components analysis with a Pearson correlation matrix to determine the number of factors to retain when dealing with ordinal data.

[pt] A presente tese é um estudo de cunho autoetnográfico de vivências sociodiscursivas em um contexto escolar público e parte do entendimento exploratório de que o papel de alunos e alunas em sala de aula extrapola a aprendizagem. Imbuída desse entendimento, propõe uma formação continuada docente coconstruída na relação com quem se ensina: os alunos e as alunas. Inserida no campo interdisciplinar da Linguística Aplicada brasileira contemporânea, a tese investiga processos sociais na dinâmica micro-macro por meio da análise de discursos narrativos. Por isso, convida praticantes de pesquisa (aluno, aluna, professoras) para Conversas com Potencial Exploratório motivadas por episódios de sala de aula vividos pela professora-pesquisadora e seus alunos e alunas. A partir das narrativas decorrentes dessas conversas, é procedida a análise dos dados, na qual se investiga, pelo posicionamento dos praticantes (entre os quais, a pesquisadora), relações de poder e entendimentos sobre ensinar e aprender. Pela análise dos dados, observam-se discrepâncias hierárquicas que persistem na relação professora-alunos ao mesmo tempo em que aprendizados são construídos no diálogo, na escuta. Tais aprendizados são ora construídos pela professora, ora percebidos nos discursos de alunos e alunas. Em ambos os casos, observa-se que o que se aprende excede conteúdos pedagógicos e aponta para a(s) qualidade(s) da(s) vida(s) em sala de aula, permitindo que temas socialmente lidos como tabu (conflitos, por exemplo) sejam discutidos e negociados na interação. Resulta, então, que essa dinâmica local aponta para repertórios globais que falam, por exemplo, sobre o lugar das emoções no espaço escolar. Além disso, nesse entrelaçar entre micro e macro, há espaço para persistências tanto quanto há para microrupturas na construção da relação-que-é-formação entre a professora e suas alunas e alunos. / [en] The present dissertation is a study inspired in the auto-ethnography of socio-discursive experiences situated in a public school context and results from the exploratory understanding that the role of students in classrooms exceeds that of learning. Guided by such an understanding, the dissertation proposes a continuous teacher development process build upon the relationship with those who learn with the teacher: the students. Inserted in the interdisciplinary field of Brazilian contemporary Applied Linguistics, the study organizes the investigation of social processes in the micro-macro dynamic through the analysis of narrative discourses. To this purpose, it invites research practitioners (students, teachers) to engage in Potentially Exploratory Conversations motivated by classroom episodes lived by the researcher. The narratives that emerged in these conversations were analysed by focusing on power relations and understandings about teaching and learning through the positioning of the research participants, including the researcher. The analysis shows that hierarchical disparities persist in the teacher-students relation while learning is built through the acts of dialoguing and listening. These learning moments or opportunities are sometimes built by the teacher and, at other moments, are noticed in the students’ discourse. In both cases, it is noticed that what is learned exceeds pedagogical content and points to the quality of life (or, the qualities of the lives) lived or experienced in the classroom. This allows for topics socially faced as taboos (conflicts, for example) to be discussed and negotiated in the interaction. As a result, this local discursive dynamic points to global repertoires that address, for example, the place of emotions in school contexts. In addition, in this embedment between micro and macro, there is room for persistencies as much as there is room for micro-fissures in the construction of the relation-that-is-development between teacher and students.

The purpose of this research was to better understand consumer knowledge, its constituents, antecedents and consequences or implications for other consumer behaviours so as to assist wine marketers and marketers of other information-intensive products with their marketing strategy development.  Wine is a complex product difficult for consumers to evaluate particularly prior to purchase but it is also a difficult product for marketers.  Wine has a very large number of both intrinsic and extrinsic attributes.  As a result of the numerous attributes and the multitude of combinations of these attributes there is a plethora of wine brands available making for a highly competitive industry and a complicated product for consumers.    Consumer knowledge affects all aspects of consumer purchasing behaviour and is thus an important phenomenon for marketers to research and understand.  Consumer knowledge also affects all aspects of the marketing strategy developed to satisfy target segments.  Marketing decision makers need to understand consumers to be able to analyze and profile segments, choose target markets and develop marketing strategies that will best align with those target markets.  Calls particularly for better understanding of different segments within the wine market provide justification for this research. The research problem was divided into three components: Consumer wine knowledge constituents, Antecedents of consumer wine knowledge and the Implications of consumer wine knowledge.  The latter component of the research problem explored the implications of consumer wine knowledge for segmentation, as well as the relationships between consumer wine knowledge and exploratory purchasing behaviour, variety-seeking behaviour and opinion leadership and opinion-seeking behaviours.  This study provides evidence of the existence of two distinct constituents of consumer knowledge i.e. what consumers know (objective knowledge) and what they think they know (subjective knowledge) and these constituents in the context of wine are significantly related.  However it is also clear that these constituents are significantly different, with different antecedents and implications for other consumer behaviours.  This study provides a visual depiction of a simplistic nomological map developed for the construct of consumer knowledge based on the studies reported in this thesis in the context of an information-intensive product such as wine.  Objective knowledge is largely driven by demographic antecedents, specifically age, gender and education while subjective knowledge is mostly driven by, or affected by consumption.  On the implications side of the map, objective knowledge significantly positively correlates with exploratory acquisition, and opinion leadership while subjective knowledge is positively related to opinion leadership and negatively to opinion-seeking behaviours.  Theoretical implications as well as recommendations for wine marketers and researchers are provided. / <p>QC 20151217</p>

Thesis (MComm)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: The analysis of multidimensional (multivariate) data sets is a very important area of research in applied statistics. Over the decades many techniques have been developed to deal with such datasets. The multivariate techniques that have been developed include inferential analysis, regression analysis, discriminant analysis, cluster analysis and many more exploratory methods. Most of these methods deal with cases where the data contain numerical variables. However, there are powerful methods in the literature that also deal with multidimensional binary and count data. The primary purpose of this thesis is to discuss the exploratory and inferential techniques that can be used for binary and count data. In Chapter 2 of this thesis we give the detail of correspondence analysis and canonical correspondence analysis. These methods are used to analyze the data in contingency tables. Chapter 3 is devoted to cluster analysis. In this chapter we explain four well-known clustering methods and we also discuss the distance (dissimilarity) measures available in the literature for binary and count data. Chapter 4 contains an explanation of metric and non-metric multidimensional scaling. These methods can be used to represent binary or count data in a lower dimensional Euclidean space. In Chapter 5 we give a method for inferential analysis called the analysis of distance. This method use a similar reasoning as the analysis of variance, but the inference is based on a pseudo F-statistic with the p-value obtained using permutations of the data. Chapter 6 contains real-world applications of these above methods on two special data sets called the Biolog data and Barents Fish data. The secondary purpose of the thesis is to demonstrate how the above techniques can be performed in the software package R. Several R packages and functions are discussed throughout this thesis. The usage of these functions is also demonstrated with appropriate examples. Attention is also given to the interpretation of the output and graphics. The thesis ends with some general conclusions and ideas for further research. / AFRIKAANSE OPSOMMING: Die analise van meerdimensionele (meerveranderlike) datastelle is ’n belangrike area van navorsing in toegepaste statistiek. Oor die afgelope dekades is daar verskeie tegnieke ontwikkel om sulke data te ontleed. Die meerveranderlike tegnieke wat ontwikkel is sluit in inferensie analise, regressie analise, diskriminant analise, tros analise en vele meer verkennende data analise tegnieke. Die meerderheid van hierdie metodes hanteer gevalle waar die data numeriese veranderlikes bevat. Daar bestaan ook kragtige metodes in die literatuur vir die analise van meerdimensionele binêre en telling data. Die primêre doel van hierdie tesis is om tegnieke vir verkennende en inferensiële analise van binêre en telling data te bespreek. In Hoofstuk 2 van hierdie tesis bespreek ons ooreenkoms analise en kanoniese ooreenkoms analise. Hierdie metodes word gebruik om data in gebeurlikheidstabelle te analiseer. Hoofstuk 3 bevat tegnieke vir tros analise. In hierdie hoofstuk verduidelik ons vier gewilde tros analise metodes. Ons bespreek ook die afstand maatstawwe wat beskikbaar is in die literatuur vir binêre en telling data. Hoofstuk 4 bevat ’n verduideliking van metriese en nie-metriese meerdimensionele skalering. Hierdie metodes kan gebruik word om binêre of telling data in ‘n lae dimensionele Euclidiese ruimte voor te stel. In Hoofstuk 5 beskryf ons ’n inferensie metode wat bekend staan as die analise van afstande. Hierdie metode gebruik ’n soortgelyke redenasie as die analise van variansie. Die inferensie hier is gebaseer op ’n pseudo F-toetsstatistiek en die p-waardes word verkry deur gebruik te maak van permutasies van die data. Hoofstuk 6 bevat toepassings van bogenoemde tegnieke op werklike datastelle wat bekend staan as die Biolog data en die Barents Fish data. Die sekondêre doel van die tesis is om te demonstreer hoe hierdie tegnieke uitgevoer word in the R sagteware. Verskeie R pakette en funksies word deurgaans bespreek in die tesis. Die gebruik van die funksies word gedemonstreer met toepaslike voorbeelde. Aandag word ook gegee aan die interpretasie van die afvoer en die grafieke. Die tesis sluit af met algemene gevolgtrekkings en voorstelle vir verdere navorsing.

Since the early 1980's there has been a heightened academic interest in the field of commitment, particularly as it relates to business relationships. Knowledge of commitment continues to advance and has begun splintering and applied into specific and narrow fields. The particular field of interest in this study surrounds commitment levels in business relationships within property and casualty insurance distribution networks. The intent of understanding and enhancing commitment levels is to allow stakeholders to explore new ways to improve profitability. This can be achieved by deepening the level of understanding and knowledge of relationship partners with a view to anticipating and fulfilling their needs better than the competition. However, commitment is intangible and involves many factors including human emotion. This increases the difficulty in comprehending the whole phenomenon of commitment. To assist in furthering the knowledge in this area, transaction cost theory is examined and applied to insurance company and broker relationships. In seeking a greater understanding of the underlying drivers of commitment, this thesis investigates the theoretical contribution of transaction cost economics theory in assessing commitment levels. The purpose is to utilize the elements of transaction costs as a means to extend the awareness of how commitment is constructed, and to search for ways to improve and strengthen these relationships. The primary research method consists of three major case studies within the Canadian property and casualty insurance distribution sector. The first case study explores the perspectives of insurance brokers in Ontario. The second study reveals the perceptions of relationship managers employed with ING Canada, the country's largest property and casualty insurance company. Lastly, the research incorporates a series of interviews with ING Canada senior executives to capture their perspectives and validate the research findings from the first two case studies. These investigations into the Canadian insurance industry have provided several outputs, chief among them is the development of a conceptual model referred to as the 'Commitment Wheel'. This model has the advantages of seating affective and calculative commitment at the centre of a moving environment of commitment enablers.

ヾ本研究之目的有三：１．說明如何利用驗證性因素分析法來克服探索性因素分析法 所無法解決的困難。２．說明如何將模式之限制設定更加一般化，以適合模式之不同 假設。３．利用矩陣語言設計程式，說明當研究者汲有套裝程式可用或已有的套裝程 式無法滿足研究上的需要時，可以矩陣語言加以克服。ゝ本研究之文獻回顧包括兩個 部分：１．估計方法之文獻回顧，旨在說明多群因素分析法和工具變項因素分析法的 估計程序和其優缺點。２．反覆算法之文獻回顧，說明可用於或曾用於驗證性因素分 析法之反覆算法及其優缺點。ゞ研究方法：本研究以類似非線性迴歸中之普通最小平 方法、一般化最小平方法和最大概似法導出配適函數，依此，再利用反覆算法估計參 數及參數之標準差。々研究內容：本研究之主要內有五，１．比較驗證性因素分析法 和探索性因素分析法在設定假設上的不同。２．說明如何確認模式。３．說明如何在 不設定限制和設定限制下估計參數及參數標準差。４．如何建構檢定統計量以檢定模 式之配適結果。５．利用ＯＬＳ、ＧＬＳ、ＭＬ三種方法來做實證。ぁ研究結果：本 研究之結果主要有四，１．不論利用ＯＬＳ、ＧＬＳ或ＭＬ來估計模式參數時，皆需 要大樣本較合適。２．利用ＯＬＳ、ＧＬＳ和ＭＬ來估計模式參數時，皆要基於常態 性的假設。３．模式利用等式和不等式來設定參數的限制，使得模式更加一般化。４ ．利用矩陣語言所設計的程式可用於實證上。

<b>Introduction:</b> Health-related websites have developed to be much more than information sites: they are used to exchange experiences and find support as well as information and advice. It is important that health professionals and website developers understand how content may impact users. This thesis documents the development and application of a tool to measure the impact of using health-related websites which contain experiential and/or factual information. <b>Methods:</b> A multi-method study with five stages. Stage 1: Questionnaire items based upon themes relating to the impact of using health-related websites were constructed following qualitative secondary analysis of 93 interviews relating to patient and carer experiences of health and a recent literature review. Items were assessed by an expert panel. Stage 2: Cognitive interviews were carried out to confirm acceptability of items. Stage 3: Item reduction steps were used to reduce the number of items. Stage 4: The validity and reliability of the remaining items were tested using traditional and modern psychometric methods. Stage 5: The new questionnaire was piloted in a randomised controlled trial. <b>Results:</b> Eighty-two items were constructed according to the key themes identified in Stage 1. Following expert and patient refinement, two independent item pools entered psychometric testing. The first item pool related to general views of using the internet in relation to health and the second item pool related to the impact of using a specific health-related website. Sub-scales and summary scores were found to have high construct validity, internal consistency and test-retest reliability. The questionnaire showed high completion rates and low counts of missing data in a trial setting. <b>Conclusion:</b> Analysis confirmed good psychometric properties in the eHIQ-Part 1 (11 items) and the eHIQ-Part 2 (26 items). Preliminary findings of trial data demonstrate the acceptability and feasibility of including the eHIQ in randomised controlled trials. This tool will enable the measurement of the impact of health-related websites containing various styles of information and support across a range conditions and facilitate their accurate evaluation in clinical trials.

This is a study on the conditions of collaborative learning in the context of UK ammonia emissions. By conducting an extensive review of over 40 scientific articles, this study identifies and synthesizes a list of nine conditions deemed necessary for successful collaborative learning processes and explores their extent and overall influence between three stakeholders involved in UK ammonia emissions. Hybrid focus group/key informant interviews provided the data for this exploration. This study suggests that the extent of these 9 conditions are present enough between the three stakeholders to initiate a collaborative learning process. By conducting further studies with a wider field of stakeholders, a collaborative learning process could identify possible ways to mitigate UK ammonia emissions.

Digitalization is a fast paced phenomenon that is recognised to be of importance for the auditing profession’s future. This study has, through an innovative approach, gathered the ideas and perspectives on the perceived future role of digitalization in relation to the auditing profession. In order to ensure that these ideas and perspectives were to be practically relevant, 14 Swedish auditors were interviewed. This study was initiated through an evident need of research about the future role of digitalization, as this role is recognized as important but rather under-theorized according to both practitioners and academics.   In order to tackle the need for research within the relatively unexplored area of digitalization in relation to the auditing profession, a dialogue with practitioners led to the creation of the following research question:    -How do auditors expect digitalization to shape the future of the auditing profession?   In order to accurately answer the constructed research question, three sub-questions were established:   - How do auditors perceive past and current changes of the auditing profession? - How do auditors perceive futures changes of the auditing profession? - How do auditors perceive the future role of digitalization?   The underlying purpose of this study was to push for a unification between the academic and practice community. To achieve this, a follow-up sub-question was generated:   - How do auditors perceive the role of academic research to shape the future of the auditing profession?   And inductive research approach was adopted for this study, in line with the epistemological standpoint of interpretivism and a constructionism ontological approach. Furthermore, this thesis was a conducted qualitative exploratory research that employed semi-structured interviews. The research strategy of this study was a combination of narrative inquiry with grounded theory in order to collect data and to generate theories for building knowledge.   The results from the interviews with the auditors generated findings that were used to answer our four sub-questions, and therefore subsequently our main research question. It was concluded that academic research was not directly used by practitioners, since it was not found usable from a practical perspective. Furthermore, it was concluded through applying change theories that digitalization is, by auditors, expected to play an important role in the future of their profession and a list of driving forces was established. Moreover, discussions on how the auditing profession and digitalization will interact in the future are disclosed in this study.

In this dissertation, I investigate interactive visual history for collaborative exploratory data analysis (EDA). In particular, I examine use of analysis history for improving the awareness of the dimension space coverage 1 2 3 to better support data exploration. Commonly, interactive history tools facilitate data analysis by capturing and representing information about the analysis process. These tools can support a wide range of use-cases from simple undo and redo to complete reconstructions of the visualization pipeline. In the con- text of exploratory collaborative Visual Analytics (VA), history tools are commonly used for reviewing and reusing past states/actions and do not efficiently support other use-cases such as understanding the past analysis from the angle of dimension space coverage. How- ever, such knowledge is essential for exploratory analysis which requires constant formulation of new questions about data. To carry out exploration, an analyst needs to understand “what has been done” versus “what is remaining” to explore. Lack of such insight can result in premature fixation on certain questions, compromising the coverage of the data set and breadth of exploration [80]. In addition, exploration of large data sets sometimes requires collaboration between a group of analysts who might be in different time/location settings. In this case, in addition to personal analysis history, each team member needs to understand what aspects of the problem his or her collaborators have explored. Such scenarios are common in domains such as science and business [34] where analysts explore large multi-dimensional data sets in search of relationships, patterns and trends. Currently, analysts typically rely on memory and/or externalization to keep track of investigated versus uninvestigated aspects of the problem. Although analysis history 4 mechanisms have the potential to assist analyst(s) with this problem, most common visual representations of history are geared towards reviewing & reusing the visualization pipeline or visualization states. I started this research with an observational user study to gain a better understanding of analysts’ history needs in the context of collaborative exploratory VA. This study showed that understanding the coverage of dimension space by using linear history 5 was cumbersome and inefficient. To address this problem, I investigated how alternate visual representations of analysis history could support this use-case. First, I designed and evaluated Footprint-I, a visual history tool that represented analysis from the angle of dimension space coverage (i.e. history of investigation of data dimensions; specifically, this approach revealed which dimensions had been previously investigated and in which combinations). I performed a user study that evaluated participants’ ability to recall the scope of past analysis using my proposed design versus a linear representation of analysis history. I measured participants’ task duration and accuracy in answering questions about a past exploratory VA session. Findings of this study showed that participants with access to dimension space coverage information were both faster and more accurate in understanding dimension space coverage information. Next, I studied the effects of providing coverage information on collaboration. To investigate this question, I designed and implemented Footprint-II, the next version of Footprint-I. In this version, I redesigned the representation of dimension space coverage to be more usable and scalable. I conducted a user study that measured the effects of presenting history from the angle of dimension space coverage on task coordination (tacit breakdown of a common task between collaborators). I asked each participant to assume the role of a business data analyst and continue a exploratory analysis work which was started by a collaborator. The results of this study showed that providing dimension space coverage information helped participants to focus on dimensions that were not investigated in the initial analysis, hence improving tacit task coordination. Finally, I investigated the effects of providing live dimension space coverage information on VA outcomes. To this end, I designed and implemented a standalone prototype VA tool with a visual history module. I used scented widgets [76] to incorporate real-time dimension space coverage information into the GUI widgets. Results of a user study showed that providing live dimension space coverage information increased the number of top-level findings. Moreover, it expanded the breadth of exploration (without compromising the depth) and helped analysts to formulate and ask more questions about their data. / Graduate / 0984 / ali.sarvghad@gmail.com