This paper studies the effects of sampling the alternative values from different distributions when studying the performance of surrogate weight methods in the additive model in multi-criteria decision analysis. Several distributions are described and tested via extensive simulation in order to quantify their effects on the performance of the surrogate weight methods. We observed that the results of the surrogate weight methods using current standard distributions for the alternative values differed surprisingly little from each other, with a few exceptions, indicating a large stability. Sampling from a more extreme distribution yielded larger differences. The behaviours of the studied surrogate weight methods themselves are, for the most part, in accordance with previous studies, showing that the choice of weight elicitation approach is a more critical factor than value distribution. Hence, we conclude that the performance of the surrogate weight methods is generally stable under a wide variety of reasonable alternative value distributions and show a case when the distribution is too skewed.