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Using factor analysis to determine why students select UWC as higher education institute.Osman, Abuelgasim Ahemd Atta-Almanan. January 2009 (has links)
<p>This study investigates the most important reasons behind the rst-year students' decision to select University of the Western Cape (UWC) as higher education institution.<br />
These reasons were organized into a few factors for easy interpretation. The data to be analyzed for this project is a subsection of the data collected during the orientation period of 2008. During the orientation week of 2008, the questionnaires were completed on a voluntary basis by new rst-year students. All questionnaires were anonymously completed and therefore the data does not contain any information that could be linked to any individual. For the purpose of this study, only the black African and coloured students were considered. The other racial groups were not analyzed due to too small sample sizes. Questionnaires with missing information on the reasons for selecting UWC were not  / nalyzed. We ended up with a sample of size 600. The data were statistically analyzed, using descriptive statistics, bivariate analyses, factor analysis, coefficient of congruence and bootstrap factor analysis. The results indicated that the most important reasons aecting students to choose UWC were identied as good academic reputation, family member's advice, UWC graduates are successful and UWC graduates get good jobs. The least important reasons were found to be not accepted anywhere, parents / family members graduated from UWC, recruited by UWC and wanted to study near to home. The results also indicated that there were significant differences among students according to population groups, parent's monthly income and grade 12 average. Factor analysis of 12 variables yielded three extracted factors upon which student decisions were based. Similarities of these three factors were tested, and a high similarity among demographic characteristics and grade 12 average were found. Additional analyses were conducted to measure the accuracy of factor analyses models constructed using Spearman and Polychoric correlation matrices. The results indicated that both correlation matrices were  / nbiased, with higher variance and higher loadings when the Polychoric correlation matrix was used to construct a factor analysis model for categorical data.</p>
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Using factor analysis to determine why students select UWC as higher education instituteOsman, Abuelgasim Ahemd Atta-Almanan January 2009 (has links)
Magister Scientiae - MSc / This study investigates the most important reasons behind the rst-year students' decision to select University of the Western Cape (UWC) as higher education institution. These reasons were organized into a few factors for easy interpretation. The data to be analyzed for this project is a subsection of the data collected during the orientation period of 2008. During the orientation week of 2008, the questionnaires were completed on a voluntary basis by new rst-year students. All questionnaires were anonymously completed and therefore the data does not contain any information that could be linked to any individual. For the purpose of this study, only the black African and coloured students were considered. The other racial groups were not analyzed due to too small sample sizes. Questionnaires with missing information on the reasons for selecting UWC were not nalyzed. We ended up with a sample of size 600. The data were statistically analyzed, using descriptive statistics, bivariate analyses, factor analysis, coefficient of congruence and bootstrap factor analysis. The results indicated that the most important reasons a ecting students to choose UWC were identi ed as good academic reputation, family member's advice, UWC graduates are successful and UWC graduates get good jobs. The least important reasons were found to be not accepted anywhere, parents / family members graduated from UWC, recruited by UWC and wanted to study near to home. The results also indicated that there were significant differences among students according to population groups, parent's monthly income and grade 12 average. Factor analysis of 12 variables yielded three extracted factors upon which student decisions were based. Similarities of these three factors were tested, and a high similarity among demographic characteristics and grade 12 average were found. Additional analyses were conducted to measure the accuracy of factor analyses models constructed using Spearman and Polychoric correlation matrices. The results indicated that both correlation matrices were nbiased, with higher variance and higher loadings when the Polychoric correlation matrix was used to construct a factor analysis model for categorical data. / South Africa
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Using Primary Dynamic Factor Analysis on repeated cross-sectional surveys with binary responses / Primär Dynamisk Faktoranalys för upprepade tvärsnittsundersökningar med binära svarEdenheim, Arvid January 2020 (has links)
With the growing popularity of business analytics, companies experience an increasing need of reliable data. Although the availability of behavioural data showing what the consumers do has increased, the access to data showing consumer mentality, what the con- sumers actually think, remain heavily dependent on tracking surveys. This thesis inves- tigates the performance of a Dynamic Factor Model using respondent-level data gathered through repeated cross-sectional surveys. Through Monte Carlo simulations, the model was shown to improve the accuracy of brand tracking estimates by double digit percent- ages, or equivalently reducing the required amount of data by more than a factor 2, while maintaining the same level of accuracy. Furthermore, the study showed clear indications that even greater performance benefits are possible.
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THE PSYCHOMETRIC PROPERTIES OF THE ARABIC VERSIONSOF THE SOCIAL NETWORKING TIME USE SCALE AND THE SOCIAL MEDIA AND ACADEMIC PERFORMANCE OF STUDENTS SCALE AMONG UNIVERSITY STUDENTS IN SAUDI ARABIAAlhaythami, Hassan Mohammed 04 August 2020 (has links)
No description available.
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Developing a Self-Respect Instrument to Distinguish Self-Respect from Self-EsteemJefferson, Sean G. 08 1900 (has links)
Throughout the scientific literature, researchers have referred to self-respect and self-esteem as being the same construct. However, the present study advocated that they exist as two distinct constructs. In this quantitative study, an instrument was developed to measure self-respect as a construct, and subsequently distinguish that self-respect is distinct from the construct of self-esteem. Exploratory factor analyses (EFA) indicated 32.60% of the variance was accounted for by the 11-item Jefferson Self-Respect instrument (JSR), which measured self-respect as a unidimensional construct. The reliability estimate of the scores from the JSR reached an acceptable α = .82. Fit indices (RMSEA = .031, SRMR = .037, CFI = .982, and TLI = .977) from the confirmatory factor analyses (CFA) signified a well-fitted hypothesized model of self-respect that existed as a unidimensional construct. Additionally, the CFA revealed that the construct of self-respect, and self-esteem was generally distinct, and the strength of the correlation between the two constructs was moderately positive (r = .62).
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Factorial invariance of an employee engagement instrument across different race groupsGallant, Wesley Herschelle 11 1900 (has links)
The overall objective of this study was to determine the factorial invariance of a South African-developed Employee Engagement Instrument (EEI) across different race groups in financial institutions. A secondary objective of this study was to determine whether race groups differ significantly with regard to the six dimensions of the employee engagement instrument.
A quantitative, cross-sectional and descriptive research design was followed in this study, using a non-probability, convenience sampling (N = 1175). The EEI was electronically administered to 285 000 businesspeople from various demographic backgrounds, which form part of a research database. The focus was respondents from financial institutions.
Descriptive and inferential statistical analysis was employed to achieve the empirical objectives of this study. Findings from the statistical analysis indicated that White and Black employees differed significantly with regards to how they are engaged by their immediate managers; however, the practical significance was small. Furthermore, the employee engagement instrument was found to be reliable and valid and the instrument was invariant across the four different race groups. By understanding how employees from different backgrounds are engaged it enables organisations to customise their engagement programmes to meet the needs of the various types of employees within the organisation, instead of applying a “one size fits all” approach to engagement programmes.
The findings of this study provided valuable insights into the importance of employee engagement in a South African context, especially for financial institutions. Finally, the study adds to the vast body of knowledge that exists with regard to employee engagement and race, both locally and internationally. / Industrial and Organisational Psychology / M. Com. (Industrial and Organisational Psychology)
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Confirmatory factor analysis of the Personal Orientation Inventory (POI)Stonefield, Nicolè 11 1900 (has links)
A survey of the field revealed a need for a Confirmatory Factor
Analysis of the Personal Orientation Inventory (POI). The two
major objectives were to understand the concept of selfactualization
and the use of the POI as a measuring instrument.
The POI correlation coefficients were used as input data for the
computer program, Linear Structural Relations (LISREL), to
perform a Confirmatory Factor Analysis.
A sample of 495 individuals was used in this research. This
sample consisted of both male and female second-year Industrial
Psychology students from various race groups.
The research concluded that the Root Mean Square Error of
Approximation (RMSEA) indicated a poor fit between the empirical
model and the empirical reality. This determined that the POI's
factor structure could not confirm the theoretical model of selfactualization.
It is acknowledged that more research needs to be conducted,
taking due consideration of bias variables and cultural
diversity. / Industrial and Organisational Psychology / M. Com. (Industrial Psychology)
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[en] PSYCHOMETRIC PROPERTIES AND THE LATENT STRUCTURE OF THE PORTUGUESE VERSION OF THE PENN STATE WORRY QUESTIONNAIRE / [pt] PROPRIEDADES PSICOMÉTRICAS E ESTRUTURA LATENTE DA VERSÃO EM PORTUGUÊS DO QUESTIONÁRIO DE PREOCUPAÇÃO DO ESTADO DA PENSILVÂNIACRISTIAN DOS SANTOS CASTILLO 20 August 2007 (has links)
[pt] O objetivo do presente trabalho consistia em traduzir o
Questionário de
Preocupação do Estado da Pensilvânia (PSWQ) para o
português e avaliar as
propriedades psicométricas e a estrutura latente desta
versão traduzida em uma amostra
representativa de universitários no Brasil para determinar
sua confiabilidade e validade
psicométricas. Um primeiro estudo utilizou 871 graduandos
de diferentes Universidades
do Rio de Janeiro apresentando uma faixa de idade de 17 a
68 anos. Uma análise
fatorial exploratória (AFE) foi realizada para examinar a
estrutura latente dos 16 itens
que compõem esta escala. Um segundo estudo utilizou 978
graduandos com as mesmas
características do estudo 1. Uma análise fatorial
confirmatória (AFC) foi usada para
inspecionar eventuais artefatos fatoriais da escala,
previamente descritos na literatura.
Os resultados indicaram que o PSWQ apresentou uma adequada
consistência interna.
No primeiro estudo, uma AFE indicou uma solução de dois
fatores. Um fator foi
relacionado com a preocupação presente e incorporou todos
os 11 itens escritos na
forma afirmativa. O outro foi associado com a preocupação
ausente e incorporou todos
os 5 itens escritos na forma negativa. No segundo estudo,
uma AFC ajustou uma
solução de três fatores. Um fator incorporou todos os
itens do PSWQ, onde os outros
dois fatores foram relacionados com os itens na afirmativa
e negativa. Coeficientes de
correlação destes dois fatores de itens na afirmativa e
negativa com o total do PSWQ e a
subescala traço do Inventário de Ansiedade Traço-Estado
sugerem que o fator composto
pelos 5 itens na negativa não contribui significativamente
para a estrutura latente do
PSWQ. A avaliação psicométrica da versão em português do
PSWQ indicou que esta
escala pode medir confiavelmente a presença do construto
de preocupação em uma
amostra não clínica. Análises de sua estrutura fatorial
sugeriram que o fator da
preocupação ausente deve ser um artefato metodológico
atribuído ao efeito da forma
escrita dos itens na negativa. / [en] Translate the Penn State Worry Questionnaire (PSWQ) to
Portuguese and
evaluate the psychometric properties and the latent
structure of the translated version in
a large Brazilian college student sample to determine its
psychometric reliability and
validity. A first study employed 871 undergraduate
students from different Universities
of Rio de Janeiro ranging from 17 to 68 years of age. An
exploratory factor analysis
(EFA) was employed to analyze its latent structure of 16
items that composes the scale.
A second study employed 978 college students with the same
characteristics from Study
1. A confirmatory factor analysis (CFA) was used to
investigate eventual factorial
artifacts of the scale previously described in the
literature. Results indicated that PSWQ
had an adequate internal consistency. In the first study,
the EFA yields a two-factor
solution. One factor was related to worry presence and
incorporated all the 11
positive-worded items stated in a non-reversed form. The
other was associated to
worry absence and incorporated all the five negative-
worded items stated in a
reversed form. In a second study, the CFA leads to a three-
factor solution. One factor
incorporated all the PSWQ items whereas the two other
factors were linked to the
reversed and non-reversed items. Correlations coefficients
of these two reversed and
non-reversed factors with the total scores of the PSWQ and
the trait subscale of the
State-Trait Anxiety Inventory suggest that the factor
composed by the five items do not
contribute in a meaningful way to the PSWQ latent
structure. Psychometric evaluation
of the Portuguese version of the PSWQ indicated that the
scale can reliably measure the
presence of the worry construct in a non-clinical sample.
Analysis of its factorial
structure suggested that the worry absence factor might be
a methodological artifact due
to a wording effect of the reversed items.
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Confirmatory factor analysis of the Personal Orientation Inventory (POI)Stonefield, Nicolè 11 1900 (has links)
A survey of the field revealed a need for a Confirmatory Factor
Analysis of the Personal Orientation Inventory (POI). The two
major objectives were to understand the concept of selfactualization
and the use of the POI as a measuring instrument.
The POI correlation coefficients were used as input data for the
computer program, Linear Structural Relations (LISREL), to
perform a Confirmatory Factor Analysis.
A sample of 495 individuals was used in this research. This
sample consisted of both male and female second-year Industrial
Psychology students from various race groups.
The research concluded that the Root Mean Square Error of
Approximation (RMSEA) indicated a poor fit between the empirical
model and the empirical reality. This determined that the POI's
factor structure could not confirm the theoretical model of selfactualization.
It is acknowledged that more research needs to be conducted,
taking due consideration of bias variables and cultural
diversity. / Industrial and Organisational Psychology / M. Com. (Industrial Psychology)
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Three essays on spectral analysis and dynamic factorsLiska, Roman 10 September 2008 (has links)
The main objective of this work is to propose new procedures for the general dynamic factor analysis<p>introduced by Forni et al. (2000). First, we develop an identification method for determining the number of common shocks in the general dynamic factor model. Sufficient conditions for consistency of the criterion are provided for large n (number of series) and T (the series length). We believe that our procedure can shed<p>light on the ongoing debate on the number of factors driving the US or Eurozone economy. Second, we show how the dynamic factor analysis method proposed in Forni et al. (2000), combined with our identification method, allows for identifying and estimating joint and block-specific common factors. This leads to a more<p>sophisticated analysis of the structures of dynamic interrelations within and between the blocks in suchdatasets.<p>Besides the framework of the general dynamic factor model we also propose a consistent lag window spectral density estimator based on multivariate M-estimators by Maronna (1976) when the underlying data are coming from the alpha mixing stationary Gaussian process. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished
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