Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

Often, all of the variables in a model are latent, random, or subject to measurement error, or there is not an obvious dependent variable. When any of these conditions exist, an appropriate method for estimating the linear relationships among the variables is Least Principal Components Analysis. Least Principal Components are robust, consistent,…

Increasingly, unpopular facilities are sited in sparsely populated areas for which data are unavailable. The Local Expert Procedure (LEP) estimates selected demographic characteristics of small, rural areas by combining the housing unit method of population estimation with random sampling and key informant ethnography. Factors affecting the…