{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":27,"n_cols":5,"rows_kept":27,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[8,2,8,3],[9,2,9,3],[10,2,10,3],[11,2,11,3],[14,2,14,3],[15,2,15,3],[19,2,19,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910826581903321"]
[null,null,"Autore",null,"Rutherford Andrew <1958->"]
[null,null,"Titolo",null,"ANOVA and ANCOVA : a GLM approach / / Andrew Rutherford"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, NJ, : Wiley, c2011"]
[null,null,"ISBN",null,"1-118-49168-8"]
[{"$nulls":4},"1-283-59290-8"]
[{"$nulls":4},"9786613905352"]
[{"$nulls":4},"1-118-49171-8"]
[null,null,"Edizione",null,"[2nd ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (360 p.)"]
[null,null,"Disciplina",null,"519.538"]
[null,null,"Soggetti",null,"Analysis of variance"]
[{"$nulls":4},"Analysis of covariance"]
[{"$nulls":4},"Linear models (Statistics)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"ANOVA and ANCOVA A GLM Approach; Contents; Acknowledgments; 1 An Introduction to General Linear Models: Regression, Analysis of Variance, and Analysis of Covariance; 1.1 Regression, Analysis of Variance, and Analysis of Covariance; 1.2 A Pocket History of Regression, ANOVA, and ANCOVA; 1.3 An Outline of General Linear Models (GLMs); 1.3.1 Regression; 1.3.2 Analysis of Variance; 1.3.3 Analysis of Covariance; 1.4 The \"\"General\"\" in GLM; 1.5 The \"\"Linear\"\" in GLM; 1.6 Least Squares Estimates; 1.7 Fixed, Random, and Mixed Effects Analyses; 1.8 The Benefits of a GLM Approach to ANOVA and ANCOVA"]
[{"$nulls":4},"1.9 The GLM Presentation 1.10 Statistical Packages for Computers; 2 Traditional and GLM Approaches to Independent Measures Single Factor ANOVA Designs; 2.1 Independent Measures Designs; 2.2 Balanced Data Designs; 2.3 Factors and Independent Variables; 2.4 An Outline of Traditional ANOVA for Single Factor Designs; 2.5 Variance; 2.6 Traditional ANOVA Calculations for Single Factor Designs; 2.7 Confidence Intervals; 2.8 GLM Approaches to Single Factor ANOVA; 2.8.1 Experimental Design GLMs; 2.8.2 Estimating Effects by Comparing Full and Reduced Experimental Design GLMs; 2.8.3 Regression GLMs"]
[{"$nulls":4},"2.8.4 Schemes for Coding Experimental Conditions 2.8.4.1 Dummy Coding; 2.8.4.2 Why Only (p - 1) Variables Are Used to Represent All "]
[{"$nulls":4},"Experimental Conditions?; 2.8.4.3 Effect Coding; 2.8.5 Coding Scheme Solutions to the Overparameterization Problem; 2.8.6 Cell Mean GLMs; 2.8.7 Experimental Design Regression and Cell Mean GLMs; 3 Comparing Experimental Condition Means, Multiple Hypothesis Testing, Type 1 Error, and a Basic Data Analysis Strategy; 3.1 Introduction; 3.2 Comparisons Between Experimental Condition Means; 3.3 Linear Contrasts; 3.4 Comparison Sum of Squares; 3.5 Orthogonal Contrasts"]
[{"$nulls":4},"3.6 Testing Multiple Hypotheses 3.6.1 Type 1 and Type 2 Errors; 3.6.2 Type 1 Error Rate Inflation with Multiple Hypothesis Testing; 3.6.3 Type 1 Error Rate Control and Analysis Power; 3.6.4 Different Conceptions of Type 1 Error Rate; 3.6.4.1 Test wise Type 1 Error Rate; 3.6.4.2 Family wise Type 1 Error Rate; 3.6.4.3 Experiment wise Type 1 Error Rate; 3.6.4.4 False Discovery Rate; 3.6.5 Identifying the \"\"Family\"\" in Family wise Type 1 Error Rate Control; 3.6.6 Logical and Empirical Relations; 3.6.6.1 Logical Relations; 3.6.6.2 Empirical Relations; 3.7 Planned and Unplanned Comparisons"]
[{"$nulls":4},"3.7.1 Direct Assessment of Planned Comparisons 3.7.2 Contradictory Results with ANOVA Omnibus F-tests and Direct Planned Comparisons; 3.8 A Basic Data Analysis Strategy; 3.8.1 ANOVA First?; 3.8.2 Strong and Weak Type 1 Error Control; 3.8.3 Step wise Tests; 3.8.4 Test Power; 3.9 The Three Basic Stages of Data Analysis; 3.9.1 Stage 1; 3.9.2 Stage 2; 3.9.2.1 Rom's Test; 3.9.2.2 Shaffer's R Test; 3.9.2.3 Applying Shaffer's R Test After a Significant F-test; 3.9.3 Stage 3; 3.10 The Role of the Omnibus F-Test; 4 Measures of Effect Size and Strength of Association, Power, and Sample Size"]
[{"$nulls":4},"4.1 Introduction"]
[null,null,null,"Sommario/riassunto","Provides an in-depth treatment of ANOVA and ANCOVA techniques from a linear model perspective  ANOVA and ANCOVA: A GLM Approach provides a contemporary look at the general linear model (GLM) approach to the analysis of variance (ANOVA) of one- and two-factor psychological experiments. With its organized and comprehensive presentation, the book successfully guides readers through conventional statistical concepts and how to interpret them in GLM terms, treating the main single- and multi-factor designs as they relate to ANOVA and ANCOVA.  The book begins with a brief history of"]