The Course Placement Service of the American College Testing Program (ACT) uses logistic regression to model the relationships between outcomes in standard college courses and placement test scores. The logistic regression results are used together with empirical test score data to obtain estimates of validity statistics (e.g., proportion of correct placement decisions), given particular hypothetical cutoff scores. Prior research has shown that the accuracy of these statistics is affected by "hard truncation," a condition in which no standard course outcome data are available for students below a certain cutoff score. Hard truncation is uncommon in actual placement systems; however, standard course outcome data typically are available for some students below the cutoff score ("soft truncation"). A soft truncation condition of 40%, for example, is one in which 40% of students below the cutoff score do not have standard course outcome data. The results of this study show that reasonably accurate estimates of validity statistics can be obtained even when 40%, and in some cases, 60% or 80%, soft truncation occurs. Moreover, the slope of the logistic regression curve and the skewness of the test score marginal distribution have little to do with the relative accuracy of validity statistics unless soft truncation exceeds 40%. Data for 6 placement groups, each containing 500 observations, were used. Appendixes present joint distributions of ACT score and college course outcome for placement groups 2 through 5 and illustrations of the effects of soft truncation on estimated success rate by placement group. (Contains 4 tables, 26 figures, and 6 references.) (SLD)