In this video, how the validity analysis (Exploratory factor analysis) is performed using SPSS, from the provision of the prerequisites to the writing of the findings, is explained in detail.
00:00 Introduction
00:46 What validity do we detect?
01:40 What analysis are we doing?
02:49 Running analysis
09:21 Reading the report
10:06 Inter-item correlation
13:43 KMO and Barlett
16:35 Common variance
18:31 Difference from model correlations
19:57 Factor structure and validity result
23:16 Factor loadings and distribution of items to factors
28:16 Reporting in Word

You can also watch:
What is validity? How is it different from reliability?:    • Güvenirlik ve Geçerlik Nedir?  
What are the validation methods?:    • Geçerlik Belirleme Yöntemleri  

Resources:
Selection of oblique and vertical rotation with principal components method: Büyüköztürk, Ş. (2011). Manual of data analysis for social sciences. Ankara: Pegem Academy. Page 126.
Inter-item correlation and the 0.0001 rule: Field, A. (2009). Discovering Statistics Using SPSS. London: SAGE. Page 657.
KMO and Barlett: Field, A. (2009). Discovering Statistics Using SPSS. London: SAGE. Page 659.
KMO should be at least 0.60: Büyüköztürk, Ş. (2011). Manual of data analysis for social sciences. Ankara: Pegem Academy. Page 126.
Common variance: Field, A. (2009). Discovering Statistics Using SPSS. London: SAGE. Page 662.
Difference from model correlations: Field, A. (2009). Discovering Statistics Using SPSS. London: SAGE. Page 664.
Determination of factors and validity: Field, A. (2009). Discovering Statistics Using SPSS. London: SAGE. Page 661.
Buyukozturk, S. (2011). Manual of data analysis for social sciences. Ankara: Pegem Academy. Pages 124-125.
Factor loads min. Taking 0.40: Field, A. (2009). Discovering Statistics Using SPSS. London: SAGE. Page 660.

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