Process / pipelineSampling

Adaptive Maximum Variation Sampling

Adaptive maximum variation sampling is a purposive qualitative sampling strategy that combines the logic of maximum variation sampling — deliberately selecting cases that differ as widely as possible on key dimensions — with an adaptive, iterative recruitment process. Rather than fixing the full sample in advance, the researcher continuously reviews emerging data to identify which types of cases are underrepresented and recruits new participants to fill those gaps, maximizing heterogeneity throughout data collection.

Find Topic with PaperMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. [Maximum variation sampling, pp. 169–183] ISBN: 978-0803937796
  2. Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. DOI: 10.2307/2289601

Related methods

ScholarGateAdaptive Maximum Variation Sampling (Adaptive Maximum Variation Purposive Sampling). Retrieved 2026-06-04 from https://scholargate.app/en/survey-methodology/adaptive-maximum-variation-sampling