  Propensity Score Matching (PSM) is an useful method to reduce the impact
ofTreatment - Selection Bias in the estimation of causal effects in
observational studies. After matching, the PSM significantly reduces the sample
under investigation, which may lead to other possible biases. In this sense, we
want to analyse the behaviour of this PSM compared with other widely used
method to deal with non-comparable groups, as is the Multivariate Regression
Model (MRM). Monte Carlo Simulations are made to construct groups with
different effects in order to compare the behaviour of PSM and MRM estimating
this effects. Also the Treatment - Selection Bias reduction for the PSM is
calculated. With the PSM a reduction in the Treatment - Selection Bias is
achieved, with a reduction in the Relative Real Treatment Effect Estimation
Error, but despite of this bias reduction and estimation error reduction, the
MRM significantly reduces more this estimation error compared with the PSM.
Also the PSM leads to a not insignificant reduction of the sample. This loss of
information derived from the matching process may lead to another not known
bias, and thus, to the inaccurate of the effect estimation compared with the
MRM.
