Repeatability of dietary patterns extracted through multivariate statistical methods: a literature review in methodological issues

References

• Arvaniti F, Panagiotakos DB. 2008. Healthy indexes in public health practice and research: a review. Crit Rev Food Sci Nutr. 48:1–11.
   PubMed Web of Science ®Google Scholar
• Bingham SA. 1987. The dietary assessment of individuals: methods, accuracy, new techniques and recommendations. Nutr Abstr Rev. 57:705–742.
   Google Scholar
• Bland MJ, Altman DG. 1986. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1:307–310.
   PubMed Web of Science ®Google Scholar
• Bountziouka V, Bathrellou E, Constantinidis TC, Polychronopoulos E, Panagiotakos DB. 2010. Repeatability of dietary patterns derived using α-priori and α-posterior methods. J Appl Biobehav Res. 15:31–68.
   Google Scholar
• Bountziouka V, Bathrellou E, Zazpe I, Ezquer L, Martínez-González MA, Panagiotakos DB. 2012. Repeatability of Food Frequency Assessment Tools in relation to the number of items and response categories included. Food Nutr Bull. 33:288–295.
   PubMed Web of Science ®Google Scholar
• Bountziouka V, Panagiotakos DB. 2010. Statistical methods used for the evaluation of reliability and validity of nutrition assessment tools used in medical research. Curr Pharm Des. 16:3770–3775.
   PubMed Web of Science ®Google Scholar
• Bountziouka V, Tzavelas G, Polychronopoulos E, Constantinidis TC, Panagiotakos DB. 2011. Validity of dietary patterns derived in nutrition surveys using a priori and a posteriori multivariate statistical methods. Int J Food Sci Nutr. 62:617–627.
   PubMed Web of Science ®Google Scholar
• Bountziouka V, Panagiotakos DB. 2012. The role of rotation type used to extract dietary patterns through principal component analysis, on their short-term repeatability. J Data Sci. 10:19–36.
   Google Scholar
• Carrol JR, Midthune D, Subar AF, Shumakovich M, Freedman LS, Thompson FE, Kipnis V. 2012. Taking advantage of the strengths of 2 different dietary assessment instruments to improve intake estimates for nutritional epidemiology. Am J Epidemiol. 175:340–347.
   PubMed Web of Science ®Google Scholar
• Cattell BR. 1966. The scree test for the number of factors. Multivar Behav Res. 1:245–276.
   PubMed Web of Science ®Google Scholar
• Cattell RB 1978. The scientific use of factor analysis in behavioral and life sciences. New York: Plenum.
   Google Scholar
• Eckart C, Gale Y. 1937. The approximation of one matrix by another one of lower rank. Psychometrika. 3:211–218.
   Google Scholar
• Ekavi NG, Pitsavos C, Yannakoulia M, Panagiotakos DB. 2013. The role of dietary patterns’ assessment in the predictive ability of cardiovascular disease risk estimation models: a review. Int J Food Sci Nutr. 65:3–8.
   PubMed Web of Science ®Google Scholar
• Fung TT, Chiuve SE, McCullough ML, Rexrode KM, Logroscino G, Hu FB. 2008. Adherence to a DASH-style diet and risk of coronary heart disease and stroke in women. Arch Intern Med. 168:713–720.
   PubMed Web of Science ®Google Scholar
• Galton F. 1888. Co-relations and their measurement. Proc R Soc Lond Ser. 45:135–145.
   Google Scholar
• Guttman L. 1954. Some necessary conditions for common factor analysis. Psychometrika. 19:149–161.
   Google Scholar
• Hernández AR, García-Villanova B, Guerra Hernández EJ, Amiano P, Azpiri M, Molina Montes E. 2015. Description of indexes based on the adherence to the Mediterranean Dietary Pattern: a review. Nutr Hospital. 32:1872–1884.
   PubMed Web of Science ®Google Scholar
• Horn JL. 1965. A rationale and test for the number of factors in factor analysis. Psychometrika. 30:179–185.
   PubMed Web of Science ®Google Scholar
• Hotteling H. 1933. Analysis of a complex of statistical variables into principal components. J Educ Psychol. 24:417–441. 498–520.
   Google Scholar
• Jackson DA. 1993. Stopping rules in principal component analysis: a comparison of heuristical and statistical approaches. Ecology. 74:2204–2214.
   Web of Science ®Google Scholar
• Kaiser FH. 1958. The varimax criterion for analytic rotation in factor analysis. Psychometrika. 23:187–240.
   Web of Science ®Google Scholar
• Kaiser FH. 1960. The application of electronic computers to factor analysis. Educ Psychol Meas. 20:141–151.
   Web of Science ®Google Scholar
• Karr JR, Martin TE. 1981. Random numbers and principal components: further searches for the unicorn? In the use of multivariate statistics in studies on wildlife habitat. In: Capen DE, editor. U.S. Forest Service Gen. Tech. Report RM-87.
   Google Scholar
• Kim S, Haines PS, Siega-Riz AM, Popkin BM. 2003. The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. J Nutr. 133:3476–3484.
   PubMed Web of Science ®Google Scholar
• Kleinbaum DG, Kupper LL, Muller KE. 1988. Variable reduction and factor analysis. Applied regression models and other multivariate methods. PWS-KENT Publishing Company, Boston, Massachusetts. Chapter 24: pp. 595–640.
   Google Scholar
• Lawley DN, Maxwell AE. 1971. Factor analysis as a statistical method. New York: Macmillan.
   Google Scholar
• Ledesma RD, Valero-Mora P. 2007. Determining the number of factors to retain in EFA: an easy-to-use computer program for carrying out parallel analysis. Available from: http://pareonline.net/getvn.asp?v=12&n=2.
   Google Scholar
• McCullough ML, Feskanich D, Stampfer MJ, Giovannucci EL, Rimm EB, Hu FB, Spiegelman D, Huneter DJ, Colditz GA, Wilet W. 2002. Diet quality and major chronic disease risk in men and women: moving toward improved dietary guidance. Am J Clin Nutr. 76:1261–1271.
   PubMed Web of Science ®Google Scholar
• Morrison FD. 1991. Multivariate statistical methods. New York: McGraw-Hill.
   Google Scholar
• Panagiotakos DB. 2008. ?-priori versus ?-posterior methods in dietary pattern analysis, a Review in nutrition epidemiology. Nutr Bull. 33:311–315.
   Google Scholar
• Pearson K. 1901. On lines and planes of closest fit to systems of point in space. Philos Mag. 2:559–572.
   Google Scholar
• Spearman CE. 1904. General intelligence objectively determined and measured. Am J Psychol. 15:201–293.
   Web of Science ®Google Scholar
• Thurstone LL. 1934. The vectors of the mind. Address of the president before the American Psychological Association. Psychol Rev. 41:1–32.
   Google Scholar
• Thurstone LL. 1947. Multiple-factor analysis. Chicago: University of Chicago Press.
   Google Scholar
• Velicer FW. 1976. Determining the number of components from the matrix of partial correlations. Psychometrika. 41:321–327.
   Web of Science ®Google Scholar