Between Dec 19, 2024 and Jan 2, 2025, datasets can be submitted to DRUM but will not be processed until after the break. Staff will not be available to answer email during this period, and will not be able to provide DOIs until after Jan 2. If you are in need of a DOI during this period, consider Dryad or OpenICPSR. Submission responses to the UDC may also be delayed during this time.
 

Missingness in longitudinal research: attrition analysis and imputation approaches in a school-based, longitudinal study of young adolescents .

Loading...
Thumbnail Image

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Missingness in longitudinal research: attrition analysis and imputation approaches in a school-based, longitudinal study of young adolescents .

Published Date

2010-08

Publisher

Type

Thesis or Dissertation

Abstract

Participant attrition and missing data are omnipresent validity threats in longitudinal research. Study attrition is especially concerning in longitudinal studies with vulnerable populations, such as students in public schools located within poor urban communities where residential mobility is often a fact of life. The current study is a secondary data analysis of the Lead Peace demonstration study. "Lead Peace" is a middle school service learning program of the Minneapolis Public School District. Student outcomes associated with Lead Peace program involvement are being evaluated by the University of Minnesota Prevention Research Center with a cohort of middle school students followed over three years beginning in the 2006-2007 school year. This evaluation included student surveys administered at four points: the beginning of 6th grade (T1), the end of 6th/beginning of 7th grade (T2), the end of 7th grade (T3), and the end of 8th grade (T4). The current study utilized data from T2, T3 and T4 surveys. The purpose of this study was two-fold: (1) to compare sub-samples of young adolescents completing surveys at one or more of three time points, and (2) to test methods for handling missing data in longitudinal studies. The primary aim was to examine similarities and differences between students who completed surveys at T2, T3 and T4 and those who did not complete surveys at one or two of these data collection points. The secondary aim was to contrast estimates from multivariate models predicting youth violence involvement using three different datasets, one that included all students present for all surveys (complete-cases) and two that included imputed data from those missing at time points T3 and T4. The primary aim was addressed through a series of comparison tests contrasting a group of students who completed all three surveys with groups who in-migrated and groups who out-migrated during the study period. Groups were compared on variables including gender, ethnicity, number of years living in one's neighborhood, number of schools in current school year, substance use, a variety of pro-social connectedness factors, bullying and violence involvement. The study's secondary aim was addressed by creating three different longitudinal datasets, one that includes all students present for all surveys (complete-case analysis) and two that include imputed data for those students missing at time points T3 and T4. Two types of data imputation, regression-imputation and multiple imputation, were used to create a second and third dataset. Comparisons were made of point estimates, standardized beta values, and standard errors generated by each dataset for a longitudinal regression model of relationships between T2 youth violence involvement, T3 neighborhood connectedness measures, and T4 youth violence involvement. Findings related to primary aim suggested that out-migrating and in-migrating groups of students were similar to those who started and stayed the duration of the Lead Peace study. Students who entered the study at T3 tended to have increased levels of disruptive behavior in their first year, but became more similar to the group of students present the entire time in the second year of surveys. Students who joined Lead Peace for only the T4 data collection point exhibited the greatest number of different characteristics across comparisons from those who were present at all time points. Data imputation models performed as hypothesized, with each having merits and drawbacks. In each dataset, T2 violence involvement predicted T4 violence involvement at statistically significant levels (p = 0.00 in each multivariate model). T3 neighborhood civic contribution predicted decreased T4 violence involvement (p = 0.03) only in the multivariate model employing the regression-imputation dataset. All other longitudinal multivariate relationships tested were not significant in multivariate models. T he current study offers a framework for understanding attrition in longitudinal research with public school students from low-income urban neighborhoods. Within these settings, students who leave a longitudinal study may be similar to students who stay for the duration of a study. In contrast, students who join a longitudinal study exhibit several differences in psychosocial and behavioral characteristics than those present for the duration of a study. Findings from this study's attrition analysis will inform investigators who are considering study designs and are making generalizations about study samples in similar research settings. The current study also adds to the growing evidence of the utility of data imputation methods to handle missing data in longitudinal research. Finally, findings offer mixed evidence of pro-social "neighborhood connectedness" as a protective factor buffering youth from violence involvement.

Description

University of Minnesota Ph.D. dissertation. August 2010. Major: Nursing. Advisor: Renee E. Sieving. 1 computer file (PDF); xii, 156 pages, appendices A-H.

Related to

Replaces

License

Collections

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Other identifiers

Suggested citation

Harpin, Scott Butler. (2010). Missingness in longitudinal research: attrition analysis and imputation approaches in a school-based, longitudinal study of young adolescents .. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/96344.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.