Multilevel Analysis Of The Pisa Data
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| Author | : Esther Sui Chu Ho |
| Publisher | : The Chinese University of Hong Kong Press |
| Total Pages | : 292 |
| Release | : 2013-12-15 |
| Genre | : Education |
| ISBN | : 9628908448 |
Multilevel analysis can help to get deeper insights into factors that may have impact on schooling outcomes assessed in PISA. In this book, multilevel analysis is applied by linking student performance to the structure and processes of both the family and the school, the two major social contexts that exert powerful influence on young people. Essential/important policy issues including parental involvement, school decentralization, and medium of instruction are examined, and the possible relationship between these policies and student's achievement in light of the evidence collected in the first three cycles of the PISA study is explored. Besides, appreciating how researchers have used multilevel analysis in a variety of ways would be an effective path to learn it. The analysis in this book will add significantly to the storehouse of knowledge about the application of multilevel analysis in assessing the quality and equality of education in East Asian societies. The findings thereof would also serve as useful references for researchers, policymakers, school administrators, and teachers.
| Author | : |
| Publisher | : Org. for Economic Cooperation & Development |
| Total Pages | : 484 |
| Release | : 2009-04-21 |
| Genre | : Business & Economics |
| ISBN | : |
Rev. ed. of: PISA 2003 data analysis manual. SPSS users. c2005.
| Author | : OECD |
| Publisher | : OECD Publishing |
| Total Pages | : 478 |
| Release | : 2009-03-31 |
| Genre | : |
| ISBN | : 9264056270 |
This publication includes detailed information on how to analyse the PISA data, enabling researchers to both reproduce the initial results and to undertake further analyses.
| Author | : Myint Swe Khine |
| Publisher | : Springer Nature |
| Total Pages | : 419 |
| Release | : 2022-04-10 |
| Genre | : Education |
| ISBN | : 9811691428 |
This edited volume documents attempts to conduct systematic and prodigious research using multilevel analysis in educational settings, and present their findings and identify future research directions. It showcases the versatility of multilevel analysis, and elucidates the unique advantages in examining complex and wide-ranging educational issues. This book brings together leading experts around the world to share their works in the field, highlighting recent advances, creative and unique approaches, and innovative methods using multilevel modeling and theoretical and practical aspects of multilevel analysis in culturally and linguistically-diverse educational contexts.
| Author | : Mack C. Shelley |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 667 |
| Release | : 2008-12-30 |
| Genre | : Education |
| ISBN | : 1402084277 |
Statistical models attempt to describe and quantify relationships between variables. In the models presented in this chapter, there is a response variable (sometimes called dependent variable) and at least one predictor variable (sometimes called independent or explanatory variable). When investigating a possible cause-and-effect type of relationship, the response variable is the putative effect and the predictors are the hypothesized causes. Typically, there is a main predictor variable of interest; other predictors in the model are called covariates. Unknown covariates or other independent variables not controlled in an experiment or analysis can affect the dependent or outcome variable and mislead the conclusions made from the inquiry (Bock, Velleman, & De Veaux, 2009). A p value (p) measures the statistical significance of the observed relationship; given the model, p is the probability that a relationship is seen by mere chance. The smaller the p value, the more confident we can be that the pattern seen in the data 2 is not random. In the type of models examined here, the R measures the prop- tion of the variation in the response variable that is explained by the predictors 2 specified in the model; if R is close to 1, then almost all the variation in the response variable has been explained. This measure is also known as the multiple correlation coefficient. Statistical studies can be grouped into two types: experimental and observational.
| Author | : Tom A. B. Snijders |
| Publisher | : SAGE |
| Total Pages | : 282 |
| Release | : 1999 |
| Genre | : Mathematics |
| ISBN | : 9780761958901 |
Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.
| Author | : Jeffrey R. Harring |
| Publisher | : IAP |
| Total Pages | : 413 |
| Release | : 2015-12-01 |
| Genre | : Education |
| ISBN | : 1681233290 |
The significance that practitioners are placing on the use of multilevel models is undeniable as researchers want to both accurately partition variance stemming from complex sampling designs and understand relations within and between variables describing the hierarchical levels of these nested data structures. Simply scan the applied literature and one can see evidence of this trend by noticing the number of articles adopting multilevel models as their primary modeling framework. Helping to drive the popularity of their use, governmental funding agencies continue to advocate the use of multilevel models as part of a comprehensive analytic strategy for conducting rigorous and relevant research to improve our nation’s education system. Advances in Multilevel Modeling for Educational Research: Addressing Practical Issues Found in Real?World Applications is a resource intended for advanced graduate students, faculty and/or researchers interested in multilevel data analysis, especially in education, social and behavioral sciences. The chapters are written by prominent methodological researchers across diverse research domains such as educational statistics, quantitative psychology, and psychometrics. Each chapter exposes the reader to some of the latest methodological innovations, refinements and state?of?the?art developments and perspectives in the analysis of multilevel data including current best practices of standard techniques. We believe this volume will be particularly appealing to researchers in domains including but not limited to: educational policy and administration, educational psychology including school psychology and special education, and clinical psychology. In fact, we believe this volume will be a desirable resource for any research area that uses hierarchically nested data. The book will likely be attractive to applied and methodological researchers in several professional organizations such as the American Educational Research Association (AERA), the American Psychological Association (APA), the American Psychological Society (APS), the Society for Research on Educational Effectiveness (SREE), and other related organizations.
| Author | : OECD |
| Publisher | : OECD Publishing |
| Total Pages | : 546 |
| Release | : 2013-12-03 |
| Genre | : |
| ISBN | : 9264201157 |
This fourth volume of PISA 2012 results examines how student performance is associated with various characteristics of individual schools and school systems.
| Author | : Lei Mee Thien |
| Publisher | : Springer |
| Total Pages | : 259 |
| Release | : 2016-03-22 |
| Genre | : Education |
| ISBN | : 9463004688 |
This is the first book regarding the issues of PISA that has been published with respect to the Southeast Asian region. It is hoped that the content of this book can benefit and provide greater understanding for readers of several important aspects: (a) country performance in PISA 2012 for each participating Southeast Asian country, (b) the need for international comparative studies from the perspective at all levels of the teaching and learning process, (c) equity and quality of education, (d) how PISA impacts on policy making, and (e) the initiatives and future directions, and challenges to improve PISA performance in the future cycles of the PISA Studies. The major issues raised in this book warrant investigation and reporting to all countries of the World, including not only those countries that were engaged in PISA 2012, but also to the approximately 200 countries that are currently in the United Nations Organisation. In these regards, the readership of this book could be extended to the educators, officers from the ministries of education, researchers, policy makers, practising teachers, lecturers in universities and teacher training institutions, postgraduate students, as well as both primary and secondary school principals and teachers.
| Author | : Tom A B Snijders |
| Publisher | : SAGE |
| Total Pages | : 369 |
| Release | : 2011-10-30 |
| Genre | : Reference |
| ISBN | : 144625433X |
The Second Edition of this classic text introduces the main methods, techniques and issues involved in carrying out multilevel modeling and analysis. Snijders and Bosker′s book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book provides step-by-step coverage of: • multilevel theories • ecological fallacies • the hierarchical linear model • testing and model specification • heteroscedasticity • study designs • longitudinal data • multivariate multilevel models • discrete dependent variables There are also new chapters on: • missing data • multilevel modeling and survey weights • Bayesian and MCMC estimation and latent-class models. This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix. This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis. Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen. Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen.
