What type of sampling allows for comparison between different groups by selecting sample members accordingly?

Stratified purposive sampling is a method that facilitates comparisons between different groups by intentionally selecting samples based on specific characteristics relevant to the study. In this approach, the population is divided into distinct subgroups or strata that share similar traits. Researchers then sample from each of these strata in a way that reflects their proportion in the overall population or according to the research goals.

This sampling method allows for a nuanced understanding of how different segments of the population may behave or respond differently, thereby enhancing the study's validity and reliability. By focusing on particular characteristics, stratified purposive sampling ensures that all relevant groups are represented, making it easier to identify differences or similarities across those groups in the analysis.

The other sampling methods listed do not provide the same level of targeted comparison. Random sampling aims for a broad representation but does not focus on specific groups, while convenience sampling often leads to bias as it relies on easily accessible participants. Systematic sampling, although structured, also lacks the targeted approach necessary for comparing specific subgroups effectively.