A comparison of two methods for analyzing longitudinal data: Tuckerized growth curves and an application of K means analysis Academic Article uri icon

abstract

  • Two longitudinal statistical methods are illustrated and compared. The first method, Tuckerized growth curve analysis (TGCA), is an extension of factor analysis, while the second method is an extension of K means analysis (KMA), a clustering technique. Both techniques make few assumptions of data and are useful for examining growth or change in longitudinal data. The two statistical methods are described and illustrated with group counseling data. The relative strengths and weaknesses of each technique are discussed.

published proceedings

  • LEARNING AND INDIVIDUAL DIFFERENCES

author list (cited authors)

  • Brossart, D. F., Parker, R., & Willson, V. L.

citation count

  • 5

complete list of authors

  • Brossart, DF||Parker, R||Willson, VL

publication date

  • January 1998