What type of sampling method is not based on randomness and often relies on existing relationships?

Snowball sampling is a non-random sampling technique that is particularly useful in studies involving hard-to-reach populations or when there is no readily available sampling frame. This method relies on existing relationships and networks to gather data. Essentially, an initial participant provides referrals to additional participants, thus creating a "snowball" effect as more individuals are included based on these connections.

In contrast, the other sampling methods mentioned all rely on randomness to ensure every member of the population has an equal chance of being selected. Simple random sampling means every individual has an equal probability of selection without any bias. Stratified random sampling involves dividing the population into subgroups and randomly selecting samples from each subgroup, ensuring representation across key variables. Systematic random sampling uses a fixed interval to select participants from an ordered list, which also incorporates randomness.

By focusing on relationships and existing connections, snowball sampling is valuable in specific research contexts where conventional random sampling may not be feasible or effective.