Open AccessUsing Integrative Data Analysis to Investigate School Climate Across Multiple Informants
Author(s) -
Kathleen V McGrath,
Elizabeth Leighton,
Mihaela Ene,
Christine DiStefano,
Diane M. Monrad
Publication year - 2019
Publication title -
educational and psychological measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.819
H-Index - 95
eISSN - 1552-3888
pISSN - 0013-1644
DOI - 10.1177/0013164419885999
Subject(s) - pooling , construct (python library) , data collection , set (abstract data type) , data science , survey data collection , psychology , data set , computer science , sociology , statistics , social science , mathematics , artificial intelligence , programming language
Survey research frequently involves the collection of data from multiple informants. Results, however, are usually analyzed by informant group, potentially ignoring important relationships across groups. When the same construct(s) are measured, integrative data analysis (IDA) allows pooling of data from multiple sources into one data set to examine information from multiple perspectives within the same analysis. Here, the IDA procedure is demonstrated via the examination of pooled data from student and teacher school climate surveys. This study contributes to the sparse literature regarding IDA applications in the social sciences, specifically in education. It also lays the groundwork for future educational researchers interested in the practical applications of the IDA framework to empirical data sets with complex model structures.