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Thomson RG, De Brún A, Flynn D, et al. Factors that influence variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke: results of a discrete choice experiment. Southampton (UK): NIHR Journals Library; 2017 Jan. (Health Services and Delivery Research, No. 5.4.)
Factors that influence variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke: results of a discrete choice experiment.
Show detailsFactor analysis using principal component analysis (PCA) with orthogonal rotation (varimax) was conducted on the six-item scale. The Kaiser–Meyer–Olkin (KMO) measure verified the sampling adequacy for the analysis, KMO = 0.83, which suggests that the sample size is adequate for factor analysis.132 Bartlett’s test of sphericity [χ2(15) = 338.95; p < 0.001] indicated that correlations between items were sufficiently large for PCA. An initial analysis was run to obtain eigenvalues for each component in the data. The results indicated that only one component had an eigenvalue of > 1 and explained 57.47% of the variance. Following inspection of the scree plot, the one component was confirmed and retained for the final analysis. Table 16 displays the factor loadings after varimax rotation. Factor loadings of > 0.55 are considered ‘good’ to ‘excellent’.133 The one-component solution suggests that the items on the scale all measure institutional culture of thrombolysis. Reliability analysis was conducted and internal consistency was high, with Cronbach’s alpha of 0.84.
- Factor analysis of Institutional Culture Scale - Factors that influence variatio...Factor analysis of Institutional Culture Scale - Factors that influence variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke: results of a discrete choice experiment
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