An Introduction to Secondary Data AnalysisDownload Powerpoint
2011-2012 Methodology Applications Series
Secondary data analysis is the analysis of data collected by an external source. Analysis of large scale secondary data sets is appealing because it is inexpensive and accessible, and because samples tend to be much larger and more representative of target populations than samples obtained by individual researchers. Nevertheless, applied educational and psychological researchers analyzing secondary data often encounter additional challenges due to complex sampling designs. This presentation will (a) discuss the advantages and disadvantages of using secondary data, (b) introduce relevant methodological considerations such as sampling weights, standard error estimation, and suppression, and (c) illustrate these concepts with examples from data sets sponsored by the National Center for Education Statistics (NCES). Funding and training opportunities will be briefly addressed.
Natalie Koziol earned her master’s in Quantitative, Qualitative, and Psychometric Methods in Educational Psychology from the University of Nebraska–Lincoln in 2010 and was awarded the 2011 Folsom Distinguished Master’s Thesis Award. She is currently a doctoral student in Quantitative, Qualitative and Psychometric Methods in the Educational Psychology Program at UNL, with appointments as a CYFS Statistics and Measurement Consultant and as instructor of an undergraduate-level statistical methods course. Her research interests include latent variable methods, particularly as they relate to issues of estimation.