Latent Variable

Vermunt, Jeroen K.; Magidson, Jay

doi:10.1002/0470013192.bsa339

Cited by 467 publications

(749 citation statements)

References 1 publication

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“…Segmentation was performed utilising the LC cluster analysis. The analysis is implemented with the LC cluster analysis software Latent GOLD 4.5 which determined the parameters of the model 1 using the maximum-posterior method (Vermunt & Magidson, 2005a, 2005b, 2005c.…”

Section: Socio-demographic and Food Spending Structurementioning

confidence: 99%

Food habits. Changes among young Italians in the last 10years

et al. 2013

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a b s t r a c tThe study aims to identify future trends in food habits by comparing the food choices made in Italy by Generation X in the year 2000 with those of Generation Y in 2009. The analysis was conducted utilising the food expenditures surveyed by the National Statistics Institute on a representative sample of consumers. Segmentation was performed using the Latent Class Clustering in order to identify the principal food patterns and their evolution in the span of a decade. The results point out some trends of homologation in food consumptions that are potentially problematic from the viewpoint of the healthy aspects. An increase is noted among the so-called savers, characterised by a diet with a high energetic density, while a decline is noted among the young ''traditionals'' who stand out for their high consumptions of fruit, vegetables and fish. Out-of-the-home consumptions become established among singles, and there is an increase of easy to prepare and ready to eat products, especially among the young people with children of Northern Italy. These elements raise several issues with regard to social, economic and health implications. Public intervention becomes fundamental to provide information and stimulate markets in orienting producers and consumers towards virtuous models, compatible with the new demands of society.

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Section: Socio-demographic and Food Spending Structurementioning

confidence: 99%

Food habits. Changes among young Italians in the last 10years

et al. 2013

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“…In order to analyze the data, first, student evaluation data were submitted to series of latent class models using a comprehensive modeling program, Latent GOLD 4.5, developed by Vermunt and Magidson (2005). The five models including 1-5 classes were analyzed by using seven indicators.…”

Section: Discussionmentioning

confidence: 99%

Investigating Student Evaluation of Teachers by Using Latent Class Analysis: A Case Study at a Tertiary Level

Üstünlüoğlu

Gungor-Culha²

2012

IJE

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Student evaluations of teaching and teacher (SET) have become the focus of extensive data collection, due to high levels of competition in education. Yet, analysis of the data collected from students has been relatively neglected in favor of evaluation. Furthermore, heterogeneity of student population with different academic background may require advanced statistical techniques, such as Latent Class Analysis (LCA), used in the context of Latent Variable Models, to disclose latent classes or structures by the manifest variables. The purpose of the study is to identify distinct groups of students based on their SET ratings and use the LCA method to discover whether there is a discrepancy in the identified classes in terms of level of success and gender. The study also aims to present a descriptive examination regarding the students who evaluated the instructors and which classes they belonged to. The following three conclusions have been drawn from this research; that different typological structures of student exist in the institution, that there are differences in the identified classes in terms of gender, and that, regardless of whether they were successful or not, students were generally positive about teachers.

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“…Ideally, variables (in this case, characteristics of knowledge transfer mechanisms and tools) within the same latent class have to be similar on certain criteria, while transfer mechanisms grouped in other different latent classes are dissimilar from each other in certain important ways (Vermunt & Magidson 2005). Latent class analysis is a statistical analysis technique for finding subtypes of related cases (latent classes) from multivariate numeric or categorical data on the basis of maximum likelihood estimation.…”

Section: A Typology Of Knowledge Transfer Mechanisms Methodological Amentioning

confidence: 99%

“…For the identification of the latent clusters, the software application Latent Gold 4.0 was employed (Vermunt & Magidson 2005). Summary fit statistics of the models are depicted in Table 8.…”

Section: Clusters Of Knowledge Transfer Mechanisms and Tools Identifiedmentioning

confidence: 99%

Refining the classification of knowledge transfer mechanisms for project-to-project knowledge sharing

Waveren

Oerlemans

Pretorius

2017

SAJEMS

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Background: The complex, unique and temporary nature of projects makes project-to-project knowledge transfer challenging and has attracted attention from both practitioners and academic scholars. This challenging nature of project-to-project knowledge transfer led to the proliferation of a host of tools and instruments (so-called knowledge transfer mechanisms) in which little structure can be discovered making selection by (project) managers a difficult task.Aim: This article aims to deal with this unstructured proliferation of knowledge transfer mechanisms by empirically categorising these transfer mechanisms, thereby reducing the number of mechanisms to groups that share a common characteristic.Setting: The study takes stock of the wide range of knowledge transfer mechanisms available and analyses them in terms of specific characteristics (e.g. explicitness or reach).Methods: A multi-method approach is used in which a multi-level latent class analysis is applied on data collected via an expert panel.Results: Five categories of transfer mechanisms could be empirically established where these mechanisms showed common characteristics.Conclusion: The taxonomy developed will allow organisations and project managers to more efficiently select appropriate transfer mechanisms for use in project-to-project knowledge transfer.

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Latent Variable

Cited by 467 publications

References 1 publication

Food habits. Changes among young Italians in the last 10years

Food habits. Changes among young Italians in the last 10years

Investigating Student Evaluation of Teachers by Using Latent Class Analysis: A Case Study at a Tertiary Level

Refining the classification of knowledge transfer mechanisms for project-to-project knowledge sharing

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