  The simplest theory describing large-scale redshift-space distortions (RSD),
based on linear theory and distant galaxies, depends on the growth of
cosmological structure, suggesting that strong tests of General Relativity can
be constructed from galaxy surveys. As data sets become larger and the expected
constraints more precise, the extent to which the RSD follow the simple theory
needs to be assessed in order that we do not introduce systematic errors into
the tests by introducing inaccurate simplifying assumptions. We study the
impact of the sample geometry, non-linear processes, and biases induced by our
lack of understanding of the radial galaxy distribution on RSD measurements.
Using LasDamas simulations of the Sloan Digital Sky Survey II (SDSS-II)
Luminous Red Galaxy (LRG) data, these effects are shown to be important at the
level of 20 per cent. Including them, we can accurately model the recovered
clustering in these mock catalogues on scales 30 -- 200 Mpc/h. Applying this
analysis to robustly measure parameters describing the growth history of the
Universe from the SDSS-II data, gives
$f(z=0.25)\sigma_8(z=0.25)=0.3512\pm0.0583$ and
$f(z=0.37)\sigma_8(z=0.37)=0.4602\pm0.0378$ when no prior is imposed on the
growth-rate, and the background geometry is assumed to follow a $\Lambda$CDM
model with the WMAP + SNIa priors. The standard WMAP constrained $\Lambda$CDM
model with General Relativity predicts
$f(z=0.25)\sigma_8(z=0.25)=0.4260\pm0.0141$ and
$f(z=0.37)\sigma_8(z=0.37)=0.4367\pm0.0136$, which is fully consistent with
these measurements.
