Bootstrapping in Data Analysis: An Overview and Example Applications
Saturday, May 29, 2010,
10:30 AM - 11:50 AM
Hampton A - B
Ohio State University
After an introductory overview of bootstrapping as an inferential data analysis tool, specific applications of bootstrapping are described and compared to more commonly use methods. Applications discussed include the estimation of intervening variable effects in path and multilevel models, factor analysis and latent variable modeling, and comparisons between groups in experimental and nonexperimental research designs.