Abstract
4 Introduction 7 Principles of Factor Analysis 8 Definition of the factor model 8 Estimation methods 12 Principal component solution of the factor model 12 Maximum likelihood solution of the factor model 13 Number of factors to retain 13 Factor rotation 14 Peculiar issues of factor analysis in nutritional epidemiology 15 Principles of Cluster Analysis 17 Similarity measures 17 Hierarchical Clustering Methods 18 Ward’s method 20 Nonhierarchical Clustering Methods 20 K-means Method 21 Choice of the number of clusters 21 Peculiar issues of cluster analysis in nutritional epidemiology 22 The choice of the distance measure has consequences on the identified clusters, which are relevant also from a nutritional standpoint. 22 Application On Data From A Case-Control Study 27 Design and participants 27 2 Statistical analysis: factor analysis 28 Variable selection 28 Factorability of the original matrix 28 Identification of dietary patterns through factor analysis 30 Estimation of factor scores 30 Choice of the number of dietary patterns to retain 31 Rotation of the identified dietary patterns 31 Naming of the identified dietary patterns 31 Evaluation of the identified solution 31 Interpretation of the identified solution 33 Risk estimates 33 Statistical analysis: cluster analysis 34 Selection of input variables 34 Examination of potential outliers 34 Choice of the number of clusters 34 Method and distance measure 35 Comparison with clustering obtained through other methods and distance measures ..... 36 Interpretation of the clustering solution 36 Risk estimates 36 Results 37 Preliminary examination of potential outliers 43 Choice of the number of clusters 44
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