In the present article, functions written in the freeware R are presented that calculate several measures from traditional signal detection theory for each individual in a sample, along with summary statistics for the sample. Bias-corrected and accelerated bootstrap confidence intervals are also produced. Arguments are made for using an alternative approach—multilevel generalized linear models—and a function is presented for it. These functions are part of the R package sdtalt, which is available on the Comprehensive R Archive Network. Recent data from memory recognition studies are used to illustrate these functions.