Section 1 : Introduction

 		Lecture 1 Introduction 0:14
Lecture 2 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf

Section 2 : Downloading and Installing Required Softwares

 		Lecture 3 Downloading and Installing SPSS 9:52
Lecture 4 Downloading and Installing AMOS 24 (Free 14 Day Trial Version) 4:12

Section 3 : Useful References

 		Lecture 5 Articles Text

Section 4 : Practice Datasets and Files Used in this Course

 		Lecture 6 Dataset used in Factor Analysis Personality Text
Lecture 7 Dropbox Link for All Resources Used Text

Section 5 : Establishing Reliability of a TestScale

 		Lecture 8 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 9 What is Reliability 3:16
Lecture 10 Reflective vs 5:19
Lecture 11 Should We Report Cronbach's Alpha or Composite Reliability 1:35
Lecture 12 Type of Reliability Test-Retest Reliability 1:53
Lecture 13 Type of Reliability Parallel Form 1:49
Lecture 14 Type of Reliability Internal Consistency Reliability 3:24
Lecture 15 Understanding Cronbach's Alpha 1:37

Section 6 : Improving Scale Reliability

 		Lecture 16 Assumptions of Cronbach's Alpha 8:50
Lecture 17 Formula of Cronbach's Alpha 2:17
Lecture 18 Range of Cronbach's Alpha 4:31
Lecture 19 Calculating Reliability Understanding Scale if an Item is Deleted Option 2:39
Lecture 20 Interpreting Case Processing Summary & Alpha Coefficient 0:46
Lecture 21 Improving Reliability of a Scale Diagnosing Missing Values 6:7
Lecture 22 Improving Reliability Diagnosing Scale Mean and Variances 2:31
Lecture 23 Improving Reliability Diagnosing Item-Total Correlations 4:42
Lecture 24 mp4 7:49
Lecture 25 Item Discrimination Index 3:48

Section 7 : Analysing Dimensionality and Factor Structure of Scale

 		Lecture 26 What is Factor Analysis 2:10
Lecture 27 Understanding Latent Variables and Indicators in FA 1:1
Lecture 28 Sample Researches Using FA in Social Science & Engineering 5:54
Lecture 29 Historical Origin of FA & Its Application in Test Construction
Lecture 30 Exploratory Factor Analysis vs 5:16
Lecture 31 Setting Data for Factor Analysis 2:33
Lecture 32 Understanding Selection Variable 2:50
Lecture 33 Univariate Descriptives & Initial Solutions Descriptive 1:19
Lecture 34 Correlation Matrix Coefficients, Significance, Determinant, KMO & Bartlett's 4:31
Lecture 35 Understanding Inverse, Reproduced, Anti-Image 3:56
Lecture 36 Extraction Method Principle Component Analysis 2:54
Lecture 37 Extraction Method Principle Axis Factoring 1:40
Lecture 38 Extraction Method Maximum Likelihood Estimation 0:47
Lecture 39 Choosing Correlation vs 8:13
Lecture 40 Interpreting Correlation Matrix & Unrotated Factor Solution 5:51
Lecture 41 Determining number of factors Scree Plot vs 7:29
Lecture 42 Factor Rotation What it is and why its done 6:26
Lecture 43 Rotation Methods Varimax, Quartimax, Equamax, Direct Oblimin, Promax 8:3
Lecture 44 Calculating Factor Scores Regression, Bartlett, Anderson-Rubin 3:46
Lecture 45 Factor Score Coefficient Matrix 1:39
Lecture 46 Missing Value Analysis Listwise, Pairwise, Replace with Mean 2:48
Lecture 47 Sort by Size & Suppressing Smaller Coefficients 6:15
Lecture 48 Project in Factor Analysis Part 1 Identifying Dimensions of Personality 14:21
Lecture 49 Project in Factor Analysis Part 2 Identifying Dimensions of Personality 15:32
Lecture 50 Project in Factor Analysis Part 3 Identifying Dimensions of Personality 5:31
Lecture 51 Project in Factor Analysis Part 4 Factor Naming 13:28
Lecture 52 Project in Factor Analysis Part 5 Reliability Analysis of Factors 22:29
Lecture 53 Project in Factor Analysis Part 6 Presenting Results in APA Style 8:52

Section 8 : Scale Validation using SPSS AMOS

 		Lecture 54 Importing EFA model in AMOS 3:52
Lecture 55 Reliability and Validity Two Sides of Model Quality 0:22
Lecture 56 Understanding Reliability and Validity 2:13
Lecture 57 What is Validity 2:8
Lecture 58 Type of Construct Validity Convergent Validity 2:31
Lecture 59 What is Average Variance Extracted (AVE) & Why AVE More than 4:35
Lecture 60 Understanding Formula for AVE Calculation 3:20
Lecture 61 Manual Calculation of AVE using Excel
Lecture 62 What is Maximum Shared squared Variance (MSV) 2:9
Lecture 63 Why MSV Should be Less Than AVE for Discriminant Validity 1:26
Lecture 64 Manual Calculation of MSV 3:7
Lecture 65 What is Average Shared squared Variance (ASV) 1:17
Lecture 66 Why ASV should be less than AVE for Discriminant Validity 1:12
Lecture 67 Manual Calculation of ASV

Section 9 : Fitting the Structural Model of Scale

 		Lecture 68 What are Indices of Model-Fit 3:22
Lecture 69 Type of Fit Indices Incremental and Absolute Fit Indices 5:6
Lecture 70 What are Incremental Fit Indices 1:56
Lecture 71 What are Absolute Fit Indices 0:52
Lecture 72 Which Indices Should I Report in Output or My Report 3:40
Lecture 73 How to Calculate Indices of Model Fit in AMOS 1:35
Lecture 74 Explaining CMIN (with Detailed Explanation of Variance-Covariance Matrix) 6:58
Lecture 75 Symbolic Expression of Null Hypothesis of Goodness of Fit Test
Lecture 76 Problem with Chi-Square Test & Why We Need Relative Chi-Square 2:33
Lecture 77 Relative Chi-Square 2:18
Lecture 78 Goodness of Fit Index (GFI) & Adjusted Goodnes of Fit Index (AGFI) 1:55
Lecture 79 Parsimony based Goodness of Fit Index (PGFI) 1:23
Lecture 80 SRMR Conceptual Explanation 1:34
Lecture 81 SRMR Calculation 1:36
Lecture 82 RMSEA Conceptual Explanation 1:44
Lecture 83 RMSEA Calculation 1:5

Section 10 : Working with AMOS Plugins Extra Section

 		Lecture 84 What are Plugins 1:7
Lecture 85 Location of plugins in AMOS 23 and Lower Versions 1:32
Lecture 86 Location of Plugins in AMOS 24 2:59
Lecture 87 Downloading AMOS Plugins from Statswiki Website (Prof
Lecture 88 Installing Four Plugins by Prof 3:55