Factor analysis & chronbach's alpha

1. rotations

1.1. non-orthogonal rotation (oblique rotation)

1.1.1. shows both the pattern & structure matrix

1.1.2. rotation that allows for correlation

1.2. orthogonal rotation

1.2.1. only 1 matrix is shown

1.2.2. rotations that assume that factors are not correlated

2. matrix

2.1. pattern matrix

2.1.1. factor loading

2.1.1.1. assign meaning to each factor

2.2. structure matrix

2.2.1. correlation between each item & each factor

2.3. factor correlation matrix

2.3.1. correlation between factors

3. Principal Component Analys (PCA)

3.1. uses the full variance of items

3.2. initial communalities = 1

4. Principal Axis Factoring (PAF)

4.1. uses only the common variance

4.2. initial communalities are not equal to 1