How to analyze reaction times and accuracy together? Is there a good way to analyze reaction times and accuracy together, other than MANOVA?

I have data from an experiment in which participants had to respond to stimuli in two different conditions in a within-subject design. And my impression is that some subjects differ in accuracy between those two conditions, while some others differ in reaction time. 
How can I test such a hypothesis?
MANOVA is definitely a bad idea given that one dv is continuous and the other is binomial. After exploring a number of different approaches to combining RT and accuracy data, I've come to conclude that the best current approach is to use linear ballistic accumulator model (e.g., see Donkin et al 2011). 

The LBA is a simple (structurally and computationally) framework that lets you speak to the different processes (info processing efficiency vs response criterion) that jointly contribute to RT and error data.

References


Donkin, C., Brown, S. &amp; Heathcote, A. (2011). Drawing conclusions from choice response time models: A tutorial using the linear ballistic accumulator. Journal of Mathematical Psychology, 55, 140-151. PDF