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Author: Lanza, Stephanie T.

Resulting in 3 citations.

1.	Lanza, Stephanie T. Coffman, Donna L. Xu, Shu
1.	Causal Inference in Latent Class Analysis Structural Equation Modeling: A Multidisciplinary Journal 20,3 (2013): 361-383. Also: http://www.tandfonline.com/doi/full/10.1080/10705511.2013.797816#.Ue6Vc3caUus Cohort(s): NLSY79 Publisher: Lawrence Erlbaum Associates ==> Taylor & Francis Keyword(s): College Enrollment; Modeling, Latent Class Analysis/Latent Transition Analysis; Propensity Scores; Substance Use Permission to reprint the abstract has been denied by the publisher.
	Bibliography Citation Lanza, Stephanie T., Donna L. Coffman and Shu Xu. "Causal Inference in Latent Class Analysis." Structural Equation Modeling: A Multidisciplinary Journal 20,3 (2013): 361-383.

2.	Lanza, Stephanie T. Collins, Linda M.
2.	A Mixture Model of Discontinuous Development in Heavy Drinking From Ages 18 to 30: The Role of College Enrollment Journal of Studies on Alcohol 67,4 (July 2006): 552-561. Also: http://www.jsad.com/jsad/article/A_Mixture_Model_of_Discontinuous_Development_in_Heavy_Drinking_From_Ages_18/878.html Cohort(s): NLSY79 Publisher: Center of Alcohol Studies, Rutgers University Keyword(s): Addiction; Alcohol Use; College Enrollment; High School Students Permission to reprint the abstract has not been received from the publisher. Objective: The purpose of this study was to illustrate the use of latent class analysis to examine change in behavior over time. Patterns of heavy drinking from ages 18 to 30 were explored in a national sample; the relationship between college enrollment and pathways of heavy drinking, particularly those leading to adult heavy drinking, was explored. Method: Latent class analysis for repeated measures is used to estimate common pathways through a stage-sequential process. Common patterns of development in a categorical variable (presence or absence of heavy drinking) are estimated and college enrollment is a grouping variable. Data were from the National Longitudinal Survey of Youth (N = 1,265). Results: Eight patterns of heavy drinking were identified: no heavy drinking (53.7%); young adulthood only (3.7%); young adulthood and adulthood (3.7%); college age only (2.6%); college age, young adulthood, and adulthood (8.7%); high school and college age (4.4%); high school, college age, and young adulthood (6.3%); and persistent heavy drinking (16.9%). Conclusions: We found no evidence that prevalence of heavy drinking for those enrolled in college exceeds the prevalence for those not enrolled at any of the four developmental periods studied. In fact, there is some evidence that being enrolled in college appears to be a protective factor for young adult and adult heavy drinking. College-enrolled individuals more often show a pattern characterized by heavy drinking during college ages only, with no heavy drinking prior to and after the college years, whereas nonenrolled individuals not drinking heavily during high school or college ages are at increased risk for adult heavy drinking. [ABSTRACT FROM AUTHOR]
	Bibliography Citation Lanza, Stephanie T. and Linda M. Collins. "A Mixture Model of Discontinuous Development in Heavy Drinking From Ages 18 to 30: The Role of College Enrollment ." Journal of Studies on Alcohol 67,4 (July 2006): 552-561.

3.	Lanza, Stephanie T. Collins, Linda M.
3.	A New SAS Procedure for Latent Transition Analysis: Transitions in Dating and Sexual Risk Behavior Developmental Psychology 44,2 (March 2008): 446-456. Also: http://psycnet.apa.org/journals/dev/44/2/446/ Cohort(s): NLSY97 Publisher: American Psychological Association (APA) Keyword(s): Adolescent Sexual Activity; Alcohol Use; Dating; Modeling, Growth Curve/Latent Trajectory Analysis The set of statistical methods available to developmentalists is continually being expanded, allowing for questions about change over time to be addressed in new, informative ways. Indeed, new developments in methods to model change over time create the possibility for new research questions to be posed. Latent transition analysis, a longitudinal extension of latent class analysis, is a method that can be used to model development in discrete latent variables, for example, stage processes, over two or more times. The current article illustrates this approach using a new SAS procedure, PROC LTA, to model change over time in adolescent and young adult dating and sexual risk behavior. Gender differences are examined, and substance use behaviors are included as predictors of initial status in dating and sexual risk behavior and transitions over time.
	Bibliography Citation Lanza, Stephanie T. and Linda M. Collins. "A New SAS Procedure for Latent Transition Analysis: Transitions in Dating and Sexual Risk Behavior ." Developmental Psychology 44,2 (March 2008): 446-456.

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