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Explanatory factor analysis (EFA) was used to reduce the number of variables.
In general the above three theories lead to principal component analysis and explanatory factor analysis.
An explanatory factor analysis is conducted to identify the perceptions toward genetic modification.
Explanatory factor analysis revealed two items with very low factor loading that were deleted.
In the explanatory factor analysis model, p denotes the number of variables (X1, X2,…,Xp) and m denotes the number of underlying factors (F1, F2,…,Fm).
The results of explanatory factor analysis confirmed the underlying construct of different reading-into-writing sub-processes (see Table 1) (for the working definitions of each cognitive phase, see Additional file 1: Appendix A).
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SS and SE executed the confirmatory factor analysis and extended explanatory factors analysis, provided support in the interpretation of the CFA-results and reviewed and contributed to the manuscript writing and revisions.
As these statistical descriptions do not include the adjustments for explanatory factors the analysis was supplemented with the results of a linear mixed model including confidence intervals for repeated yearly observations in order to investigate for possible confounders.
In spite of the above concerns, the size of our sample is considered excellent for explanatory and confirmatory factor analysis.
Critically, when entering devaluation sensitivity as an explanatory factor in the analysis of the two-stage decision task, we observed a significant three-way interaction between reward, transition, and devaluation sensitivity (Table 3).
Strong evidence of collinearity amongst the explanatory variables required a factor analysis to be undertaken.
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