NDLI: Ecological-Inference-Based Latent Growth Models: Modeling Changes of Alienation

Please wait, while we are loading the content...

Reversible Relationship between Quantitative and Qualitative Data in Self-Consciousness Research: A Normative Semiotic Model for the Phenomenological Dialogue between Data and Capta

Postal Surveys of Doctors’ Careers: Who Writes Comments and What do they Write About?

Quality and Quantity : Volume 39, Issue 1, February 2005

Quality and Quantity : Volume 38

Quality and Quantity : Volume 37

Quality and Quantity : Volume 36

Quality and Quantity : Volume 35

Quality and Quantity : Volume 34

Quality and Quantity : Volume 33

Quality and Quantity : Volume 32

Quality and Quantity : Volume 31

Ecological-Inference-Based Latent Growth Models: Modeling Changes of Alienation

Content Provider	Springer Nature Link
Author	Yang, Chih Chien Yang, Chih Chiang Yeh, Kuang Hui
Copyright Year	2005
Abstract	Ecological-inference-based statistical methods employ aggregated (ecological) data to approximately infer individual-level structures of interests when individual-level data were not available. Under the same conceptual frames, we introduce the ecological-inference-based latent growth model (EI-LGM) to analyze cross-years latent trends of a general population when longitudinally collected data were not available. We showed both the substantive values and methodological feasibilities of EI-LGMs. Substantively, we analyze results from several Taiwan Social Change Surveys (TSCS) to show the cross-years latent trends using a subscale of alienation psychological characteristics. Not only the cross-years movements of measurement constructs of the scale were shown, the trends of latent factors were revealed as well. More importantly, these trends can be formally tested under the frameworks of EI-LGMs. Statistically, EI-LGMs were implemented under the weighted least square (WLS) approaches because of the dichotomous outcomes of the subscale. We demonstrate some of the estimation methods as well as some cautions of interpreting EI-LGMs using the estimated results.
Starting Page	125
Ending Page	135
Page Count	11
File Format	PDF
ISSN	00335177
Journal	Quality and Quantity
Volume Number	39
Issue Number	2
e-ISSN	15737845
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2005-01-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Ecological-inference latent growth model Structural equation models categorical data alienations Methodology of the Social Sciences
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Social Sciences

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Confirmatory and Structural Categorical Latent Variables Models

Evaluating estimation methods for ordinal data in structural equation modeling

Investigating the Number of Non-linear and Multi-modal Relationships Between Observed Variables Measuring Growth-oriented Atmosphere

Structural equation modeling and the latent linearity hypothesis in social and behavioral research

Treating ordinal data: a comparison between rating scale and structural equation models

Analyzing Change Among Developmental Stages with Categorical Models

Comparing maximum likelihood and PLS estimates for structural equation modeling with formative blocks

Testing structural equation models: the impact of error variances in the data generating process

Value-based performance excellence model for higher education institutions

Ecological-Inference-Based Latent Growth Models: Modeling Changes of Alienation

Similar Documents

Confirmatory and Structural Categorical Latent Variables Models

Evaluating estimation methods for ordinal data in structural equation modeling

Investigating the Number of Non-linear and Multi-modal Relationships Between Observed Variables Measuring Growth-oriented Atmosphere

Structural equation modeling and the latent linearity hypothesis in social and behavioral research

Treating ordinal data: a comparison between rating scale and structural equation models

Analyzing Change Among Developmental Stages with Categorical Models

Comparing maximum likelihood and PLS estimates for structural equation modeling with formative blocks

Testing structural equation models: the impact of error variances in the data generating process

Value-based performance excellence model for higher education institutions

Ecological-Inference-Based Latent Growth Models: Modeling Changes of Alienation