This study examined the effects of multicomponent, random-frequency maskers and broadband-noise maskers on intensity discrimination at 1000 Hz. Maskers and signals were 200 ms, presented simultaneously. In the first set of conditions, thresholds were measured for the detection of a 1000-Hz tone in the presence of 40 or 60 dB SPL random-frequency or noise maskers, with extensive training of listeners with the random-frequency masker to assure stable effects of masker-frequency uncertainty. The random-frequency maskers had two, six, or ten components chosen at random from a large frequency range (300-3000 Hz, excluding a 160-Hz band around 1000 Hz). For these maskers, performance across the four listeners was very similar, showing large effects of masker-frequency uncertainty. For noise maskers, performance matched predictions for energy-based masking. In the second and third sets of conditions, intensity discrimination was measured at 1000 Hz for pedestals ranging from 40 to 80 dB SPL, first in isolation and then in the presence of the maskers. The pattern of results for intensity discrimination in quiet showed the expected near miss to Weber's Law, but poorer performance than typically observed. The addition of broadband-noise maskers had little effect on performance. However, random-frequency maskers degraded performance in nearly all conditions, with the size of the effect dependent on the level of the pedestal relative to the masker. Considering the pedestal as a tonal masker, the data were fitted with various models of combined masking. A simple power-law model provided excellent fits, with exponents ranging from 0.24 to 0.35 for the multicomponent maskers, but 1.0 (linear) for the noise. The results support models positing that the effects of individual maskers undergo nonlinear transformation before they are added, independent of the mechanisms which produce these effects. Because random-frequency maskers presumably produce informational (uncertainty-based) masking, the nonlinearity in this case appears central rather than peripheral.