Arious types of growth models within the developmental sciences; several recent examples include Brown, Meadows, and Elder (2007), McCoach, O’Connell, Reis, and Levitt (2006), Owens and Shaw (2003), and Williams, Conger, and Blozis (2007). Next, there are many well-developed online resources available that provide fully worked examples with empirical data and associated computer code; specific Web site addresses come and go, so the best strategy is to enter relevant terms in any major search engine and proceed from there. Finally, there are an increasing number of workshops available around the country that are focused on the theory and application of growth modeling within the social sciences; again, specifics change with time, but a bit of careful online searching will provide a current summary of available workshops. And if all else fails, send one of us an email and we’ll try to point you in the right direction.CONCLUSIONWe have only briefly touched on just a few of the many interesting topics associated with the potential for growth models to help us gain a better understanding of individual differences in developmental change. Important remaining issues include growth modelsJ Cogn Dev. Author manuscript; available in PMC 2011 July 7.Curran et al.Pagewith binary or discrete outcomes (e.g., Mehta et al., 2004), incorporating alternative metrics of time (e.g., Mehta West, 2000), using growth trajectories as predictors (e.g., B. O. Muth Curran, 1997; Seltzer, Choi, Thum, 2003), estimating Peretinoin supplier statistical power for growth models (e.g., B. O. Muth Curran; L. K. Muth B. O. Muth , 2002), and the estimation of hybrid autoregressive and change score models (Bollen Curran, 2004; McArdle, 2001). Growth models offer a plethora of exciting opportunities for testing theoretically derived hypotheses in ways not previously possible. Despite the strength and flexibility of these methods, even greater care must be taken to ensure that the estimated growth model maximally corresponds to the underlying developmental theory (e.g., Curran Willoughby, 2003). Any disjoint that exists between the I-CBP112 clinical trials theoretical model and the statistical model only serves to undermine our ability to draw empirically informed conclusions about our theory under study. Despite this caveat, growth models have a tremendous amount to offer to a broad array of developmental research endeavors and represent a powerful set of tools to help us continue to propel forward as a science.NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
NIH Public AccessAuthor ManuscriptJ Adolesc Res. Author manuscript; available in PMC 2011 September 7.Published in final edited form as: J Adolesc Res. 2010 May ; 25(3): 465?93. doi:10.1177/0743558410361372.NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript”It Turned My World Upside Down”: Latino Youths’ Perspectives on ImmigrationLinda K. Ko and Krista M. Perreira University of North Carolina, Chapel HillAbstractFew studies have examined the migration and acculturation experiences of Latino youth in a newly emerging Latino community, communities that historically have had low numbers of Latino residents. This study uses in-depth interview data from the Latino Adolescent, Migration, Health, and Adaptation (LAMHA) project, a mixed-methods study, to document the experiences of Latino youth (ages 14?8) growing up in one emerging Latino community in the South ?North Carolina. Using adolescent’s own word.Arious types of growth models within the developmental sciences; several recent examples include Brown, Meadows, and Elder (2007), McCoach, O’Connell, Reis, and Levitt (2006), Owens and Shaw (2003), and Williams, Conger, and Blozis (2007). Next, there are many well-developed online resources available that provide fully worked examples with empirical data and associated computer code; specific Web site addresses come and go, so the best strategy is to enter relevant terms in any major search engine and proceed from there. Finally, there are an increasing number of workshops available around the country that are focused on the theory and application of growth modeling within the social sciences; again, specifics change with time, but a bit of careful online searching will provide a current summary of available workshops. And if all else fails, send one of us an email and we’ll try to point you in the right direction.CONCLUSIONWe have only briefly touched on just a few of the many interesting topics associated with the potential for growth models to help us gain a better understanding of individual differences in developmental change. Important remaining issues include growth modelsJ Cogn Dev. Author manuscript; available in PMC 2011 July 7.Curran et al.Pagewith binary or discrete outcomes (e.g., Mehta et al., 2004), incorporating alternative metrics of time (e.g., Mehta West, 2000), using growth trajectories as predictors (e.g., B. O. Muth Curran, 1997; Seltzer, Choi, Thum, 2003), estimating statistical power for growth models (e.g., B. O. Muth Curran; L. K. Muth B. O. Muth , 2002), and the estimation of hybrid autoregressive and change score models (Bollen Curran, 2004; McArdle, 2001). Growth models offer a plethora of exciting opportunities for testing theoretically derived hypotheses in ways not previously possible. Despite the strength and flexibility of these methods, even greater care must be taken to ensure that the estimated growth model maximally corresponds to the underlying developmental theory (e.g., Curran Willoughby, 2003). Any disjoint that exists between the theoretical model and the statistical model only serves to undermine our ability to draw empirically informed conclusions about our theory under study. Despite this caveat, growth models have a tremendous amount to offer to a broad array of developmental research endeavors and represent a powerful set of tools to help us continue to propel forward as a science.NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
NIH Public AccessAuthor ManuscriptJ Adolesc Res. Author manuscript; available in PMC 2011 September 7.Published in final edited form as: J Adolesc Res. 2010 May ; 25(3): 465?93. doi:10.1177/0743558410361372.NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript”It Turned My World Upside Down”: Latino Youths’ Perspectives on ImmigrationLinda K. Ko and Krista M. Perreira University of North Carolina, Chapel HillAbstractFew studies have examined the migration and acculturation experiences of Latino youth in a newly emerging Latino community, communities that historically have had low numbers of Latino residents. This study uses in-depth interview data from the Latino Adolescent, Migration, Health, and Adaptation (LAMHA) project, a mixed-methods study, to document the experiences of Latino youth (ages 14?8) growing up in one emerging Latino community in the South ?North Carolina. Using adolescent’s own word.
