227607 Comparison of weighted versus non-weighted path analysis in adolescent health risk behavior

Wednesday, November 10, 2010 : 12:30 PM - 12:50 PM

Lynn Agre, MPH, PhD , School of Social Work/RUTCOR, Rutgers University, Piscataway, NJ
N. Andrew Peterson, PhD , School of Social Work, Rutgers University, New Brunswick, NJ
Large-scale national surveys often provide a raw weight variable, that when applied without transformation, yields no change in statistical results, thus leading to spurious conclusions about relationships between predictors and outcomes. For example, most research studies using various components of the National Longitudinal Survey on Youth (NLSY) data sets to test hypotheses, do not employ a weighting technique or post-stratification procedure to normalize the sample against the population from which it is drawn. Therefore, this paper illustrates how an algebraic weight formula introduced by Oh and Scheuren (1983), can be used in path analysis to elucidate the relationship between underlying psychosocial mechanisms and health risk behaviors among adolescents in the 1998 NLSY Young Adult cohort. This project, then, investigates the relationship between self-assessed risk perception or risk proneness and how that perception affects the likelihood of an adolescent to engage in substance use and sexual behavior, partitioned into clusters by mother's educational attainment. To control for oversampling of under represented racial/ethnic groups, mathematically adjusted design weights are implemented in the calculation of the covariance matrices, comparing non-normalized versus normalized path analysis results. The impact of ignoring weights leading to serious bias in parameter estimates, with the underestimation of standards errors will be discussed. This research makes an important contribution by using a weighted case approach in testing different samples of youth by race/ethnicity and mother's educational attainment. Determining policy initiatives and objectives requires that the data be representative of the population, ensured by applying the weight formula.

Learning Areas:
Biostatistics, economics
Diversity and culture
Planning of health education strategies, interventions, and programs
Public health or related public policy
Social and behavioral sciences
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
Evaluate how the implementation versus the non-implementation of an algebraic data weighting technique can alter statistical results reported in scientific literature.

Keywords: Adolescent Health, Methodology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am qualified to be an abstract Author on the content contained in this research because all data analysis was performed as part of a Ph.D. thesis research project.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.