Methodology development
My quantitative work has focused on various aspects of applied statistical methods to address challenges arising from handling missing data. My substantive emphasis on missing data emerged during my graduate work as I encountered an enormous gap that continues to get larger between academic research on advanced techniques and our ability to deliver these techniques to applied researchers. I have led simulation-based research in this area and contributed to best practice recommendations for applied researchers (Howard, Rhemtulla, & Little, 2015; Nicholson, Deboeck, & Howard, 2017; Zhou, Gao, & Howard, 2017). In 2012, I was awarded a research grant by the Society for Multivariate Experimental Psychology for the special emphasis of this work on multivariate approaches to the measurement and analysis of substantive problems.
Substantive research
In addition to my quantitative work, I have conducted extensive substantive research using structural equation modeling techniques as a general data analytic approach to studying individual, developmental, and socio-contextual differences (Chan et al., 2013; Desai et al., 2018; Greenwood, Buzhardt, Walker, Howard, & Anderson, 2011; Greenwood et al., 2013; Law, Fisher, Howard, Levy, & Pain, 2017; David Okech, Hansen, Howard, Anarfi, & Burns, 2018; D Okech, Howard, Child, & Work, 2013; Stein et al., 2017). In support of my substantive work, my graduate experiences with Todd Little included in depth training in an array of advanced multivariate statistical techniques. Much of this training focused on methodological issues surrounding aspects of complex developmental processes. As a result, my current research covers several topics that are integrated under an over-arching goal to eliminate over-simplified data analytic practices as limitations of research by delivering responsive, efficient, and high-quality modern alternatives.