  We develop and test an algorithm to rescale a simulated dark-matter particle
distribution or halo catalogue from a standard gravity model to that of a
modified gravity model. This method is based on that of Angulo & White but with
some additional ingredients to account for (i) scale-dependent growth of linear
density perturbations and (ii) screening mechanisms that are generic features
of viable modified gravity models. We attempt to keep the method as general as
possible, so that it may plausibly be applied to a wide range of modified
theories, although tests against simulations are restricted to a subclass of
$f(R)$ models at this stage. We show that rescaling allows the power spectrum
of matter to be reproduced at the $\sim 3$ per cent level in both real and
redshift space up to $k=0.1h\,\mathrm{Mpc}^{-1}$ if we change the box size and
alter the particle displacement field; this limit can be extended to
$k=1h\,\mathrm{Mpc}^{-1}$ if we additionally alter halo internal structure. We
simultaneously develop an algorithm that can be applied directly to a halo
catalogue, in which case the halo mass function and clustering can be
reproduced at the $\sim 5$ per cent level. Finally we investigate the
clustering of halo particle distributions, generated from rescaled halo
catalogues, and find that a similar accuracy can be reached.
