01519cam a22002654a 4500991001707169707536060620s2006 nyua b 001 0 eng d1593852746b13414525-39ule_instSet. Economiaita150.1519535422Brown, Timothy A.614441Confirmatory factor analysis for applied research /Timothy A. BrownNew York :Guilford Press,c2006xviii, 475 p. :ill. ;24 cmMethodology in the social sciencesInclude riferiemnti bibliografici (p. 439-454) e indiceIntroduction -- The common factor model and exploratory factor analysis -- Introduction to CFA -- Specification and interpretation of CFA models -- CFA model revision and comparison -- CFA of multitrait-multimethod matrices -- CFA with equality constraints, multiple groups, and mean structures -- Other types of CFA models : higher-order factor analysis, scale reliability evaluation, and formative indicators -- Data issues in CFA : missing, non-normal, and categorical data -- Statistical power and sample sizeFactor analysis.b1341452526-02-0720-06-06991001707169707536LE025 ECO 150 BRO01.0112025000128217le025-E48.36-l- 00000.i1431108203-11-06Confirmatory factor analysis for applied research1092007UNISALENTOle02520-06-06ma -engnyu0005456nam 2200649Ia 450 991078465820332120230329180035.01-280-72899-X97866107289920-08-046650-8(CKB)1000000000364049(EBL)282095(OCoLC)437175620(SSID)ssj0000310315(PQKBManifestationID)11235353(PQKBTitleCode)TC0000310315(PQKBWorkID)10288635(PQKB)10478305(Au-PeEL)EBL282095(CaPaEBR)ebr10155854(CaONFJC)MIL72899(MiAaPQ)EBC282095(EXLCZ)99100000000036404920060905d2007 uy 0engur|n|---|||||txtrdacontentcrdamediacrrdacarrierStatistical parametric mapping the analysis of functional brain images /editors, Karl Friston [et al.]London :Academic,2007.1 online resource (689 pages) illustrationsDescription based upon print version of record.1-4933-0095-4 0-12-372560-7 Includes bibliographical references and index.Front Cover; Statistical Parametric Mapping; Copyright Page; Table of Contents; Acknowledgements; Part 1 Introduction; Chapter 1 A short history of SPM; INTRODUCTION; THE PET YEARS; THE fMRI YEARS; THE MEG-EEG YEARS; REFERENCES; Chapter 2 Statistical parametric mapping; INTRODUCTION; SPATIAL TRANSFORMS AND COMPUTATIONAL ANATOMY; STATISTICAL PARAMETRIC MAPPING AND THE GENERAL LINEAR MODEL; TOPOLOGICAL INFERENCE AND THE THEORY OF RANDOM FIELDS; EXPERIMENTAL AND MODEL DESIGN; INFERENCE IN HIERARCHICAL MODELS; CONCLUSION; REFERENCES; Chapter 3 Modelling brain responses; INTRODUCTIONANATOMICAL MODELS; STATISTICAL MODELS; MODELS OF FUNCTIONAL INTEGRATION; CONCLUSION; REFERENCES; Part 2 Computational anatomy; Chapter 4 Rigid Body Registration; INTRODUCTION; RE-SAMPLING IMAGES; RIGID BODY TRANSFORMATIONS; WITHIN-MODALITY RIGID REGISTRATION; BETWEEN-MODALITY RIGID REGISTRATION; REFERENCES; Chapter 5 Non-linear Registration; INTRODUCTION; OBJECTIVE FUNCTIONS; LARGE DEFORMATION APPROACHES; ESTIMATING THE MAPPINGS; SPATIAL NORMALIZATION IN THE SPM SOFTWARE; EVALUATION STRATEGIES; REFERENCES; Chapter 6 Segmentation; INTRODUCTION; THE OBJECTIVE FUNCTION; OPTIMIZATION; REFERENCESChapter 7 Voxel-Based Morphometry; INTRODUCTION; PREPARING THE DATA; STATISTICAL MODELLING AND INFERENCE; REFERENCES; Part 3 General linear models; Chapter 8 The General Linear Model; INTRODUCTION; THE GENERAL LINEAR MODEL; INFERENCE; PET AND BASIC MODELS; fMRI MODELS; APPENDIX 8.1 THE AUTOREGRESSIVE MODEL OF ORDER 1 PLUS WHITE NOISE; APPENDIX 8.2 THE SATTERTHWAITE APPROXIMATION; REFERENCES; Chapter 9 Contrasts and Classical Inference; INTRODUCTION; CONSTRUCTING MODELS What should be included in the model?; CONSTRUCTING AND TESTING CONTRASTS; CONSTRUCTING AND TESTING F-CONTRASTSCORRELATION BETWEEN REGRESSORS; DESIGN COMPLEXITY; SUMMARY; APPENDIX 9.1 NOTATION; APPENDIX 9.2 SUBSPACES; APPENDIX 9.3 ORTHOGONAL PROJECTION; REFERENCES; Chaper 10 Covariance Components; INTRODUCTION; SOME MATHEMATICAL EQUIVALENCES; ESTIMATING COVARIANCE COMPONENTS; CONCLUSION; REFERENCES; Chapter 11 Hierarchical Models; INTRODUCTION; TWO-LEVEL MODELS; PARAMETRIC EMPIRICAL BAYES; NUMERICAL EXAMPLE; BELIEF PROPAGATION; DISCUSSION; REFERENCES; Chapter 12 Random Effects Analysis; INTRODUCTION; RANDOM EFFECTS ANALYSIS; FIXED EFFECTS ANALYSIS; PARAMETRIC EMPIRICAL BAYES; PET DATA EXAMPLEfMRI DATA EXAMPLE; DISCUSSION; APPENDIX 12.1 EXPECTATIONS AND TRANSFORMATIONS; REFERENCES; Chapter 13 Analysis of Variance; INTRODUCTION; ONE-WAY BETWEEN-SUBJECT ANOVA; ONE-WAY WITHIN-SUBJECT ANOVA; TWO-WAY WITHIN-SUBJECT ANOVAs; GENERALIZATION TO M-WAY ANOVAs; fMRI BASIS FUNCTIONS; DISCUSSION; APPENDIX 13.1 THE KRONECKER PRODUCT; APPENDIX 13.2 WITHIN-SUBJECT MODELS; REFERENCES; Chapter 14 Convolution Models for fMRI; INTRODUCTION; THE HAEMODYNAMIC RESPONSE FUNCTION (HRF); TEMPORAL BASIS FUNCTIONS; TEMPORAL FILTERING AND AUTOCORRELATION; NON-LINEAR CONVOLUTION MODELS; A WORKED EXAMPLE; REFERENCESIn an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to mBrainImagingMathematical modelsBrain mappingStatisticsGraphic methodsBrainImagingMathematical models.Brain mapping.StatisticsGraphic methods.611.810222Friston K. J(Karl J.)1497187MiAaPQMiAaPQMiAaPQBOOK9910784658203321Statistical parametric mapping3722237UNINA