  Combining several independent measurements of the same physical quantity is
one of the most important tasks in metrology. Small samples, biased input
estimates, not always adequate reported uncertainties, and unknown error
distribution make a rigorous solution very difficult, if not impossible. For
this reason, many methods to compute a common mean and its uncertainty were
proposed, each with own advantages and shortcomings. Most of them are variants
of the weighted average (WA) approach with different strategies to compute WA
and its standard deviation. Median estimate became also increasingly popular
during recent years. In this paper, these two methods in most widely used
modifications are compared using simulated and real data. To overcome some
problems of known approaches to compute the WA uncertainty, a new combined
estimate has been proposed. It has been shown that the proposed method can help
to obtain more robust and realistic estimate suitable for both consistent and
discrepant measurements.
