  Sub-millimetre dust emission provides information on the physics of
interstellar clouds and dust. Noise can produce anticorrelation between the
colour temperature T_C and the spectral index beta. This must be separated from
the intrinsic beta(T) relation of dust. We compare methods for the analysis of
the beta(T) relation. We examine sub-millimetre observations simulated as
simple modified black body emission or using 3D radiative transfer modelling.
In addition to chi^2 fitting, we examine the results of the SIMEX method, basic
Bayesian model, hierarchical models, and one method that explicitly assumes a
functional form for beta(T). All methods exhibit some bias. Bayesian method
shows significantly lower bias than direct chi^2 fits. The same is true for
hierarchical models that also result in a smaller scatter in the temperature
and spectral index values. However, significant bias was observed in cases with
high noise levels. Beta and T estimates of the hierarchical model are biased
towards the relation determined by the data with the highest S/N ratio. This
can alter the recovered beta(T) function. With the method where we explicitly
assume a functional form for the beta(T) relation, the bias is similar to the
Bayesian method. In the case of an actual Herschel field, all methods agree,
showing some degree of anticorrelation between T and beta.
  The Bayesian method and the hierarchical models can both reduce the
noise-induced parameter correlations. However, all methods can exhibit
non-negligible bias. This is particularly true for hierarchical models and
observations of varying signal-to-noise ratios and must be taken into account
when interpreting the results.
