  The chromatic contamination that arises from photospheric heterogeneities
e.g. spots and faculae on the host star presents a significant noise source for
exoplanet transmission spectra. If this contamination is not corrected for, it
can introduce substantial bias in our analysis of the planetary atmosphere. We
utilise two stellar models of differing complexity, StARPA and ASteRA, to
explore the biases introduced by stellar contamination in retrieval under
differing degrees of stellar activity. We use the retrieval framework TauREx3
and a grid of 27 synthetic, spot-contaminated transmission spectra to
investigate potential biases and to determine how complex our stellar models
must be in order to accurately extract the planetary parameters from
transmission spectra. The input observation is generated using the more complex
model (StARPA), in which the spot latitude is an additional, fixable parameter.
This observation is then fed into a combined stellar-planetary retrieval which
contains a simplified stellar model (ASteRA). Our results confirm that the
inclusion of stellar activity parameters in retrieval minimises bias under all
activity regimes considered. ASteRA performs very well under low to moderate
activity conditions, retrieving the planetary parameters with a high degree of
accuracy. For the most active cases, characterised by larger, higher
temperature contrast spots, some minor residual bias remains due to ASteRA
neglecting the interplay between the spot and the limb darkening effect. As a
result of this, we find larger errors in retrieved planetary parameters for
central spots (0 degrees) and those found close to the limb (60 degrees) than
those at intermediate latitudes (30 degrees).
