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Exploratory Factor Analysis - KMO and Bartlett's Test


Uzorak dijela rada: Exploratory Factor Analysis - KMO and Bartlett's Test

EFA - Exploratory Factor Analysis

EFA - Exploratory Factor Analysis 

1.The KayserMeyerOlkin KMO value should be higher than 0.5%  

and the Bartlett spherical value should be significant with a pvalue less than 0,5%

 

see the file: xxxxxxxxxxxxxxxx-OK.xlsx

 

Black text (with language repairs/correction) in the work, and remove background color.

 

5. The last stage of exploratory analysis is verify if the correct number of factors extracted is higher than 0.6.

 

Tests of assumptions.

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

,749

Bartlett's Test of Sphericity

Approx. Chi-Square

4989,535

df

741

Sig.

0,000

 

 

 

Should be significant (less than .05), p<0,001 indicating that the correlation matrix is significantly different from an identity matrix, in which correlations between variables are all zero.

 Kaiser-Meyer-Olkin Measure of Sampling Adequacy is 0,749. Should be greater than 0.60 indicating sufficient items for each factor.

 2. The commonality for every value should be higher than 0.4% ( Extraction )

 These communalities represent the relation between the variable and all other variables (i.e., the squared multiple correlation between the item and all other items).

 

Communalities

 

Initial

BC1 - The more expensive cars are my choice.

,538

BC2 - The higher the price of a car, the better its quality.

,897

BC3 - I prefer to buy the best-selling car brands.

,991

BC4 - The most advertised luxury car brands are my choices.

,938

BC5 - I am willing to pay higher prices for famous luxury car brands.

,925

BC6 - I care about well-known brand names rather than their quality.

,991

BC7 - I prefer to buy foreign luxury car brands than local brands.

,845

MA8 - It makes me feel comfortable when I have things that impress people.

,683

MA9 - I think acquiring luxury cars can be seen as an achievement in life.

,808

.....

Extraction Method: Principal Axis Factoring.

 EFA - Exploratory Factor Analysis

3. The total variance explained for factors have to be greater than 60%  (here is 70,117%)

 Eigenvalues refer to the variance explained or accounted for.

64,733% of the variance is accounted for by the first ten factors.

Percent of variance for each component before rotation.

Percent of variance for each component after rotation.

 

Total Variance Explained

Factor

Initial Eigenvalues

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

10,776

27,632

27,632

5,018

12,867

12,867

2

4,830

12,384

40,016

4,808

12,329

25,196

3

3,521

9,028

49,044

4,520

11,591

36,787

EFA - Exploratory Factor Analysis - Scree Plot - Rotated Factor Matrix

EFA - Exploratory Factor Analysis - Scree Plot - Rotated Factor Matrix

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