Alternative techniques for analyzing student outcomes were investigated. Two traditional statistical methods (one-way analysis of variance and two-way analysis of variance) were compared with an innovative input-output analysis. The input-output analysis is a two-step analysis consisting of a regression analysis to determine the relationships among input and output variables and an analysis of variance of the residuals grouped by treatment to determine treatment effect. Student outcome data used in the study were generated in a typical classroom experiment comparing three different methodologies of presenting material to students. Pre- and post-measures of student achievement on a final exam were taken. Some measures of student input characteristics, including grade point average, age, sex, year in school, and residential status, were also taken. While the traditional analysis techniques failed to show any treatment effects, the input-output technique showed one of the treatments to be superior to the others. It is suggested that the traditional analysis of change scores in experimental research may not be directly applicable to most research conducted on students. The treatment effects on student outcomes may well be a function of input characteristics and an interaction over time for individual students, which are not always discernable with traditional statistical analysis techniques. However, the input-output analysis allows for these problems by including other input characteristics in the analysis and allowing for the separation of data by individuals. It is concluded that student outcome research could benefit from the application of the input-output technique. (SC)