Hardware Reference
In-Depth Information
Q1.1 had provoked some comments during data collection because some people
were reluctant to recognize this practice. Comparing with descriptive analysis (section
4.1) Q1.1 was confirmed as a real fact (90.6%) and its influence on testing is high
enough (only the 12,60% rank influence as none). Although it is an important factor,
it is not related to the scale here presented: maybe this question should be better for-
mulated. Anyway more research is needed to verify the importance of this factor.
Q3.5 experienced problems due to people without specific testing training. 63.8%
of the respondents considered it as a real fact but the influence on testing is not clear
because the data are very similar for the three categories.
4.2.3 Exploratory Factorial Analysis (EFA)
EFA enables to identify the underlying structure of the relations obtaining a predictive
validation of the model. To investigate acceptability of factorial analysis results the
Table 7.
EFA Results for the model
EFA Loadings (after varimax rotation)
a
Factor
C1
C2
C3
C4
C5
Q1.1.
,673
Q1.2.
,382
,590
Q2.1
,812
Q2.2
,602
,328
Q2.3
,367
,302
,572
Q2.4
,715
Q2.5
,850
Q3.1
,824
Q3.2
,728
Q3.3
,446
,368
,347
Q3.4
,487
,471
Q3.5
,513
,372
Q3.6
,562
,325
Q4.1
,448
,565
Q4.2
,430
,576
Q5.1
,646
Q5.2
,701
Q5.3
,685
Q5.4
,376
,408
Q5.5
,658
,353
Q5.6
,820
Q6.1
,673
Q6.2
,382
,590
Cronbach´ alpha
0.908
Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy
0.853
1099,9(df = 210)
b
Bartlett's Test of Sphericity (Approx. Chi-Square)
Correlation Matrix Determinant
9,06E-005
Note: EFA=Exploratory Factor Analysis, loadings < 0.32 not shown;
a.Total variance extracted by the five factors = 60,995%, b. p<0.001
