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1. Full Text Three Cs in Measurement Models: Causal Indicators, Composite Indicators, and Covariates
by Bollen, Kenneth A and Bauldry, Shawn
Psychological methods, ISSN 1082-989X, 9/2011, Volume 16, Issue 3, pp. 265 - 284
Measurement | Composite indicators | Factor analysis | Structural equation modeling | Causal indicators | Formative indicators | Psychology, Multidisciplinary | Psychology | Social Sciences | Structural Equation Models | Computation | Statistical Analysis | Expertise | Latent Variables | Fundamental and applied biological sciences. Psychology | Psychometrics. Statistics. Methodology | Biological and medical sciences | Psychology. Psychoanalysis. Psychiatry | Statistics. Mathematics | Psychology. Psychophysiology | Psychology - methods | Self Concept | Humans | Middle Aged | Male | Factor Analysis, Statistical | Models, Statistical | Causality | Health Status | Methods | Research | Index Medicus | factor analysis | causal indicators | composite indicators | formative indicators | structural equation modeling | measurement
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2. Full Text A Hybrid Enhanced Scatter Search—Composite I-Distance Indicator (eSS-CIDI) Optimization Approach for Determining Weights Within Composite Indicators
by Maricic, Milica and Egea, Jose A and Jeremic, Veljko
Social indicators research, ISSN 0303-8300, 7/2019, Volume 144, Issue 2, pp. 497 - 537
Composite I-distance indicator approach | Public Health | Social Sciences | Human Geography | Quality of Life Research | Microeconomics | Composite indicators | Bootstrap | Enhanced Scatter Search | Sociology, general | Weighting scheme | Optimization | Algorithms | Usage | Mathematical optimization | Analysis | Methods | Social indicators | Policy making | Constraints | Social research | Weighting | Ranking | Readiness | Capabilities | Approaches | Bootstrap method | Public opinion
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3. Full Text AN INTRODUCTION TO 'BENEFIT OF THE DOUBT' COMPOSITE INDICATORS
by LAURENS CHERCHYE and WILLEM MOESEN and NICKY ROGGE and TOM VAN PUYENBROECK
Social indicators research, ISSN 0303-8300, 5/2007, Volume 82, Issue 1, pp. 111 - 145
Patents | Operations research | Technology | Environmental policy | Handbooks | Value judgments | Benchmarking | Composite indices | ORIGINAL PAPER | Data normalization | Term weighting | composite indicators | Human Geography | Sociology | data envelopment analysis | Quality of Life Research | Microeconomics | Social Sciences, general | performance benchmarking | Public Health/Gesundheitswesen | technology | Composite indicators | Performance bench marking | Data envelopment analysis | Data Analysis | Weighted Scores | Social Indicators | Credibility | Multiple Regression Analysis | Methodology | History, theory and methodology | Benchmarks | Research | Studies | Mathematical models | Technological change
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4. Full Text Weights and importance in composite indicators: Closing the gap
by Becker, William and Saisana, Michaela and Paruolo, Paolo and Vandecasteele, Ine
Ecological indicators, ISSN 1470-160X, 09/2017, Volume 80, pp. 12 - 22
Correlation | Sensitivity analysis | Gaussian process | Splines | Smoothing | Optimisation | Composite indicators | Environmental Sciences & Ecology | Life Sciences & Biomedicine | Biodiversity Conservation | Biodiversity & Conservation | Science & Technology | Environmental Sciences | Case studies | Sustainable development | Environmental auditing | Analysis
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5. Full Text In Defense of Causal-Formative Indicators: A Minority Report
by Bollen, Kenneth A and Diamantopoulos, Adamantios
Psychological methods, ISSN 1082-989X, 9/2017, Volume 22, Issue 3, pp. 581 - 596
composites | causal indicators | structural equation models | formative indicators | measurement models | Psychology, Multidisciplinary | Psychology | Social Sciences | Psychology - methods | Reproducibility of Results | Factor Analysis, Statistical | Models, Statistical | Causality | Humans | Index Medicus | factor analysis
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6. Full Text A common weight MCDA–DEA approach to construct composite indicators
by Hatefi, S.M and Torabi, S.A
Ecological economics, ISSN 0921-8009, 2010, Volume 70, Issue 1, pp. 114 - 120
Composite indicators | Multi criteria decision analysis | Common weights | Data envelopment analysis | Economics | Environmental Studies | Social Sciences | Life Sciences & Biomedicine | Business & Economics | Environmental Sciences & Ecology | Ecology | Science & Technology | Environmental Sciences | Composite indicators Data envelopment analysis Common weights Multi criteria decision analysis | Decision-making | Analysis
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7. Full Text Farmland abandonment in Europe: Identification of drivers and indicators, and development of a composite indicator of risk
by Terres, Jean-Michel and Scacchiafichi, Luigi Nisini and Wania, Annett and Ambar, Margarida and Anguiano, Emeric and Buckwell, Allan and Coppola, Adele and Gocht, Alexander and Källström, Helena Nordström and Pointereau, Philippe and Strijker, Dirk and Visek, Lukas and Vranken, Liesbet and Zobena, Aija
Land use policy, ISSN 0264-8377, 12/2015, Volume 49, pp. 20 - 34
Composite indicator | Farmland abandonment | Common agricultural policy | Land management | Europe | To be checked by Faculty | Environmental Studies | Environmental Sciences & Ecology | Life Sciences & Biomedicine | Science & Technology | Automobile drivers | Rural development | Agricultural land | Sustainable development
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8. Full Text Evaluating Effect, Composite, and Causal Indicators in Structural Equation Models
by Kenneth A. Bollen
MIS quarterly, ISSN 0276-7783, 6/2011, Volume 35, Issue 2, pp. 359 - 372
Statistical significance | Statistical variance | Error rates | Research Commentary | Variable coefficients | Collinearity | Coefficients | Structural equation models | Modeling | Parametric models | Estimators | Measurement | Validity | Composites | Causal indicators | Reflective indicators | Scale construction | Formative indicators | Effect indicators | Computer Science, Information Systems | Information Science & Library Science | Social Sciences | Technology | Computer Science | Business & Economics | Management | Science & Technology | Structural equation modeling | Research | Information systems | Studies | Causality | Models
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9. Full Text A note on Sigma–Mu efficiency analysis as a methodology for evaluating units through composite indicators
by Tsionas, Mike G
European journal of operational research, ISSN 0377-2217, 11/2020, Volume 286, Issue 3, pp. 1187 - 1196
Composite indicators | Sigma-Mu efficiency | Stochastic multi-attribute acceptability analysis | Decision processes | Bayesian analysis | Business & Economics | Operations Research & Management Science | Social Sciences | Management | Technology | Science & Technology | Case studies | Markov processes | Monte Carlo method | Analysis | Methods
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10. Full Text Bayesian network modelling of hierarchical composite indicators
by Requejo-Castro, David and Giné-Garriga, Ricard and Pérez-Foguet, Agustí
The Science of the total environment, ISSN 0048-9697, 06/2019, Volume 668, pp. 936 - 946
Systematic methodology | Water, sanitation and hygiene (WaSH) | Composite indicators (CIs) | Interlinkages | Bayesian networks | Environmental Sciences & Ecology | Life Sciences & Biomedicine | Science & Technology | Environmental Sciences | Models | Analysis | Sanitation | Hygiene | Green technology | Bayesian statistical decision theory | Water | Bayesian Networks | interlinkages | systematic methodology | composite indicators | Estadística bayesiana | Desenvolupament humà i sostenible | Aigua | Àrees temàtiques de la UPC | sanitation and hygiene
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