The resources needed to conduct high-quality and large-scale survey research are often beyond the reach of institutional researchers and higher education analysts. However, the National Center for Education Statistics (NCES) provides many national student surveys that researchers can utilize. We outline four NCES studies--the High School…

The sophisticated analytical techniques available to institutional researchers give them an array of procedures to estimate a causal effect using observational data. But as many quantitative researchers have discovered, access to a wider selection of statistical tools does not necessarily ensure construction of a better analytical model. Moreover,…

Multilevel modeling provides several advantages over traditional ordinary least squares regression analysis; however, reporting results to stakeholders can be challenging. This article suggests some strategies for presenting complex, multilevel data and statistical results to institutional and higher education decision makers. The article is…

In this article, the author argues that current strategies to study and understand students' identities fall short of fully capturing their complexity. A multi-dimensional perspective and a mixed-methods approach can reveal nuance that is missed with current approaches. The author offers an illustration of how mixed-methods research can promote a…

As a tour de force, data mining is likely to gain wider use in the next few years. To facilitate this transition, we make several recommendations addressed to both institutional research professionals and the Association of Institutional Research.

The data collected in higher education research are not always quantitative or continuous. Statistical methods using the log-linear model provide the institutional researcher with a powerful set of tools for addressing research questions when data are categorical. (Author/MSE)

The value of qualitative assessment approaches has been underestimated primarily because they are often juxtaposed against long-standing quantitative traditions and the widely accepted premise that the best research produces generalizable and statistically significant findings. Institutional researchers avoid qualitative methods for at least three…

Even the application of such mainstays of the institutional researcher's statistical tool kit as the t test and ANOVA is not always as straightforward as it seems. The researcher must first check to see that the underlying methodological and statistical assumptions are being met. (Author)

The ultimate goal of the institutional researcher is not always to test a research hypothesis, but more often simply to find an appropriate model to gain an understanding of the underlying characteristics and interrelationships of the data. Exploratory data analysis provides a means of accomplishing this. (Author)

Among the varied analytical challenges institutional researchers face, examining faculty pay may be one of the most vexing. Although the literature on faculty compensation analysis dates back to the 1970s (Loeb and Ferber, 1971; Gordon, Morton, and Braden, 1974; Scott, 1977; Braskamp and Johnson, 1978; McLaughlin, Smart, and Montgomery, 1978),…

Path analysis and linear structural relations (LISREL) provide the institutional researcher with some extremely powerful statistical tools. However, they must be applied and interpreted carefully with a full understanding of their limitations and the statistical assumptions on which they are based. (Author)

Campuses should act on salary equity issues before litigation arises. Campuses must resolve database problems, unfocused studies, problems in data interpretations, and constraints on implementing findings if they are to take timely actions. Internally motivated monitoring and court-ordered monitoring are discussed. (Author/MLW)

Many do not consider the effect that missing data have on their survey results nor do they know how to handle missing data. This chapter offers strategies for handling item-missing data and provides a practical example of how these strategies may affect results. The chapter concludes with recommendations for preventing and dealing with missing…