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1. |
Record Nr. |
UNINA9910792358203321 |
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Titolo |
Contours of citizenship [[electronic resource] ] : women, diversity and practices of citizenship / / edited by Margaret Abraham ...[et al.] |
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Pubbl/distr/stampa |
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Farnham, Surrey, England ; ; Burlington, Vt., : Ashgate Pub. Company, c2010 |
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ISBN |
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1-315-57406-3 |
1-317-16015-0 |
1-317-16014-2 |
1-282-52497-6 |
9786612524974 |
0-7546-9527-1 |
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Descrizione fisica |
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1 online resource (233 p.) |
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Collana |
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Gender in a global/local world |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Women - Political activity |
Citizenship |
Women - Social conditions |
Women's rights |
Political rights |
Diversity in the workplace |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Cover; Contents; List of Figures; List of Tables; Notes on Contributors; Acknowledgments; 1 Rethinking Citizenship with Women in Focus; 2 Less Preferred Workers and Citizens in the Making; 3 Globalization, Work, and Citizenship: The Call Centre Industry in India; 4 Female Ethnic Entrepreneurship in Spain; 5 "Becoming a Citizen": Albanian Women's Civic Education and Political Engagement in Greece; 6 The Globalizing Era and Citizenship Rights for Indigenous Australian Women; 7 Post-Colonial Women's Citizenship: Between Identity and Social-Class |
8 Mobilization Matters: Moving Immigrant and Latina Women into the Public Sphere9 Citizenship, Gender Equality and the Limits of Law Reform in South Africa; 10 Citizenship Divided, Education Deprived; 11 |
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"Liberation" and the Margins: The Greek Cypriot Experience; 12 Agency and Citizenship in Cross-Border Marriages; Index |
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Sommario/riassunto |
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This book examines the complexity of citizenship in historical and contemporary contexts. It draws on empirical research from a range of countries, contexts and approaches in addressing women and citizenship in a global/local world and covers a selection of diverse issues. This rich collection informs our understanding of the pitfalls and possibilities for women from the persistence and changes in the contours of citizenship. |
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2. |
Record Nr. |
UNINA9911020143103321 |
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Autore |
Berger Martijn P. F |
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Titolo |
An introduction to optimal designs for social and biomedical research / / Martijn P.F. Berger, Weng Kee Wong |
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Pubbl/distr/stampa |
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Hoboken, NJ, : Wiley, 2009 |
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ISBN |
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9786612188893 |
9781282188891 |
1282188895 |
9780470746912 |
0470746912 |
9780470746929 |
0470746920 |
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Descrizione fisica |
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1 online resource (348 p.) |
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Collana |
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Statistics in Practice ; ; v.83 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Social sciences - Research |
Biology - Research |
Optimal designs (Statistics) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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An Introduction to Optimal Designs for Social and Biomedical Research; Contents; Preface; Acknowledgements; 1 Introduction to designs; 1.1 Introduction; 1.2 Stages of the research process; 1.2.1 Choice of a 'good' design; 1.3 Research design; 1.3.1 Choice of independent |
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variables and levels; 1.3.2 Units of analysis; 1.3.3 Variables; 1.3.4 Replication; 1.4 Types of research designs; 1.5 Requirements for a 'good' design; 1.5.1 Statistical conclusion validity; 1.5.2 Internal validity; 1.5.3 Control of (unwanted) variation; 1.6 Ethical aspects of design choice |
1.7 Exact versus approximate designs1.8 Examples; 1.8.1 Radiation dosage example; 1.8.2 Designs for the Poggendorff and Ponzo illusion experiments; 1.8.3 Uncertainty about best .tting regression models; 1.8.4 Designs for a priori contrasts among composite faces; 1.8.5 Designs for calibration of item parameters in item response theory models; 1.9 Summary; 2 Designs for simple linear regression; 2.1 Design problem for a linear model; 2.1.1 The design; 2.1.2 The linear regression model; 2.1.3 Estimation of parameters and efficiency; 2.2 Designs for radiation-dosage example |
2.3 Relative efficiency and sample size2.4 Simultaneous inference; 2.5 Optimality criteria; 2.5.1 D-optimality criterion; 2.5.2 A-optimality criterion; 2.5.3 G-optimality criterion; 2.5.4 E-optimality criterion; 2.5.5 Number of distinct design points; 2.6 Relative efficiency; 2.7 Matrix formulation of designs for linear regression; 2.8 Summary; 3 Designs for multiple linear regression analysis; 3.1 Design problem for multiple linear regression; 3.1.1 The design; 3.1.2 The multiple linear regression model; 3.1.3 Estimation of parameters and ef.ciency; 3.2 Designs for vocabulary-growth study |
3.3 Relative efficiency and sample size3.4 Simultaneous inference; 3.5 Optimality criteria for a subset of parameters; 3.6 Relative efficiency; 3.7 Designs for polynomial regression model; 3.7.1 Exact D-optimal designs for a quadratic regression model; 3.7.2 Scale dependency of A- and E-optimality criteria; 3.8 The Poggendorff and Ponzo illusion study; 3.9 Uncertainty about best .tting regression models; 3.10 Matrix notation of designs for multiple regression models; 3.10.1 Design for regression models with two independent variables |
3.10.2 Design for regression models with two non-additive independent variables3.11 Summary; 4 Designs for analysis of variance models; 4.1 A typical design problem for an analysis of variance model; 4.1.1 The design; 4.1.2 The analysis of variance model; 4.1.3 Formulation of an ANOVA model as a regression model; 4.2 Estimation of parameters and efficiency; 4.2.1 Measures of uncertainty; 4.3 Simultaneous inference and optimality criteria; 4.4 Designs for groups under stress study; 4.4.1 A priori planned unequal sample sizes; 4.4.2 Not planned unequal sample sizes |
4.5 Specific hypotheses and contrasts |
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Sommario/riassunto |
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The increasing cost of research means that scientists are in more urgent need of optimal design theory to increase the efficiency of parameter estimators and the statistical power of their tests. The objectives of a good design are to provide interpretable and accurate inference at minimal costs. Optimal design theory can help to identify a design with maximum power and maximum information for a statistical model and, at the same time, enable researchers to check on the model assumptions. This Book:Introduces optimal experimental design in an accessible format.Pro |
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