In this paper, the author develops a new class of discrete-time, discrete-covariate models for modeling nonproportionality in event-history data within the log-multiplicative framework. The models specify nonproportionality in hazards to be a log-multiplicative product of two components: a nonproportionality pattern over time and a nonproportionality level per group. Illustrated with data from the U.S. National Longitudinal Mortality Study (Rogot et al. 1988) and from the the 1988 June Current Population Survey (Wu and Tuma 1990), the log-multiplicative models are shown to be natural generalizations of proportional hazards models and should be applicable to a wide range of research areas.