This article develops a procedure for the path analysis of ordinal variables using only ordinal statistics and presents an ordinal path analysis of data previously analyzed by Sewell and Armer (1966a). Substantively, it shows that when ordinal statistics and path analysis are used, neighborhood context has very important direct and indirect effects on college plans. This is true when neighborhood socioeconomic status is trichotomous or dichotomous. Methodologically, it demonstrates that path analysis techniques can be successfully applied to ordinal data using ordinal statistics rather than assuming equal-interval scales and applying interval statistics, or using dummy variables. Possibly, the small effect of neighborhood context reported by Sewell and Armer is a consequence of their ignoring a curvilinear relationship between neighborhood context and college plans, their assuming interval data, and their use of a linear multiple correlation model when in fact their data did not conform to the underlying assumptions.