Psychology
Multilevel modeling approaches to the study of LGBT-parent families: Methods for dyadic data analysis
Document Type
Book Chapter
Abstract
While obtaining information from multiple members of a family can enhance researchers— understanding of families, it can also present complications when trying to analyze the data, as most traditional statistical methods assume that data originate from independent sources. An additional problem arises when examining data from partners in same-sex couples, which are often “indistinguishable” as they cannot be distinguished on the basis of some characteristic (e.g., gender) meaningful to the analysis. This chapter introduces approaches to analyzing data from “indistinguishable” partners using multilevel modeling for both cross-sectional and longitudinal analysis. It also discusses ways to examine data from multiple informants—for instance, when both mothers in lesbian-parent families report on their child's well-being. Examples are drawn from the authors— recent projects to illustrate the statistical concepts and difficulties.
Publication Title
LGBT-Parent Families: Innovations in Research and Implications for Practice
Publication Date
2013
First Page
307
Last Page
323
ISBN
9781461445562,9781461445555
DOI
10.1007/978-1-4614-4556-2_20
Keywords
multilevel modeling, data analysis, multiple family members, lesbian & gay & bisexual & transgender parent families, research methods
Repository Citation
Smith, Juli Anna Z.; Sayer, Aline G.; and Goldberg, Abbie E., "Multilevel modeling approaches to the study of LGBT-parent families: Methods for dyadic data analysis" (2013). Psychology. 392.
https://commons.clarku.edu/faculty_psychology/392