Latent Variable Modeling and Applications to Causality:
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
1997
|
| Schriftenreihe: | Lecture Notes in Statistics
120 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | This volume gathers refereed papers presented at the 1994 UCLA conference on "Latent Variable Modeling and Application to Causality. " The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contributions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability conditions. Muthen studies longitudinal hierarchichal models with latent variables and treats the time vector as a variable rather than a level of hierarchy. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordinal latent variables. Arminger looks at autoregressive structures and Bock treats factor analysis models for categorical data |
| Beschreibung: | 1 Online-Ressource (VII, 281p) |
| ISBN: | 9781461218425 9780387949178 |
| ISSN: | 0930-0325 |
| DOI: | 10.1007/978-1-4612-1842-5 |
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Datensatz im Suchindex
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| discipline | Mathematik |
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| indexdate | 2024-07-10T01:21:05Z |
| institution | BVB |
| isbn | 9781461218425 9780387949178 |
| issn | 0930-0325 |
| language | English |
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| publishDate | 1997 |
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| series2 | Lecture Notes in Statistics |
| spelling | Latent Variable Modeling and Applications to Causality edited by Maia Berkane New York, NY Springer New York 1997 1 Online-Ressource (VII, 281p) txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Statistics 120 0930-0325 This volume gathers refereed papers presented at the 1994 UCLA conference on "Latent Variable Modeling and Application to Causality. " The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contributions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability conditions. Muthen studies longitudinal hierarchichal models with latent variables and treats the time vector as a variable rather than a level of hierarchy. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordinal latent variables. Arminger looks at autoregressive structures and Bock treats factor analysis models for categorical data Statistics Statistics, general Statistik Analyse latenter Strukturen (DE-588)4142341-0 gnd rswk-swf Latente Variable (DE-588)4166860-1 gnd rswk-swf Kausalanalyse (DE-588)4163511-5 gnd rswk-swf Pfadmodell (DE-588)4238807-7 gnd rswk-swf 1\p (DE-588)1071861417 Konferenzschrift gnd-content Pfadmodell (DE-588)4238807-7 s Latente Variable (DE-588)4166860-1 s 2\p DE-604 Analyse latenter Strukturen (DE-588)4142341-0 s 3\p DE-604 Kausalanalyse (DE-588)4163511-5 s 4\p DE-604 Berkane, Maia edt Lecture Notes in Statistics 120 (DE-604)BV036592911 120 https://doi.org/10.1007/978-1-4612-1842-5 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 4\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Latent Variable Modeling and Applications to Causality Lecture Notes in Statistics Statistics Statistics, general Statistik Analyse latenter Strukturen (DE-588)4142341-0 gnd Latente Variable (DE-588)4166860-1 gnd Kausalanalyse (DE-588)4163511-5 gnd Pfadmodell (DE-588)4238807-7 gnd |
| subject_GND | (DE-588)4142341-0 (DE-588)4166860-1 (DE-588)4163511-5 (DE-588)4238807-7 (DE-588)1071861417 |
| title | Latent Variable Modeling and Applications to Causality |
| title_auth | Latent Variable Modeling and Applications to Causality |
| title_exact_search | Latent Variable Modeling and Applications to Causality |
| title_full | Latent Variable Modeling and Applications to Causality edited by Maia Berkane |
| title_fullStr | Latent Variable Modeling and Applications to Causality edited by Maia Berkane |
| title_full_unstemmed | Latent Variable Modeling and Applications to Causality edited by Maia Berkane |
| title_short | Latent Variable Modeling and Applications to Causality |
| title_sort | latent variable modeling and applications to causality |
| topic | Statistics Statistics, general Statistik Analyse latenter Strukturen (DE-588)4142341-0 gnd Latente Variable (DE-588)4166860-1 gnd Kausalanalyse (DE-588)4163511-5 gnd Pfadmodell (DE-588)4238807-7 gnd |
| topic_facet | Statistics Statistics, general Statistik Analyse latenter Strukturen Latente Variable Kausalanalyse Pfadmodell Konferenzschrift |
| url | https://doi.org/10.1007/978-1-4612-1842-5 |
| volume_link | (DE-604)BV036592911 |
| work_keys_str_mv | AT berkanemaia latentvariablemodelingandapplicationstocausality |