Maximum Variation Sampling

Maximum Variation Sampling is a purposive sampling technique that deliberately selects cases exhibiting the greatest diversity across key dimensions of a phenomenon to capture a full range of variations and identify central themes or patterns common to all instances.

231

Publications

10.4K

Citations

866

Authors

415

Institutions

Publications per year

2017–2026

125

Variants

Maximum Variation Purposive Sampling

Authors

866

  1. SZ
    Sue Ziébland

    University of Oxford, United Kingdom

    8 publications · 924 citations

    8

    h-index

  2. AC
    Alison Chapple

    University of Oxford, United Kingdom

    6 publications · 807 citations

    6

    h-index

  3. DR
    Damien Ridge

    University of Westminster, United Kingdom

    4 publications · 179 citations

    4

    h-index

  4. TC
    Tina Cartwright

    University of Westminster, United Kingdom

    3 publications · 80 citations

    3

    h-index

  5. SK
    Saravana Kumar

    University of South Australia, Australia

    3 publications · 116 citations

    3

    h-index

1–5 of 866

Venues

  1. BMJ Open

    9 publications · 466 citations

    9

    h-index

  2. BMC Health Services Research

    8 publications · 236 citations

    8

    h-index

  3. PubMed

    Repository · 8 publications · 367 citations

    8

    h-index

  4. PLoS ONE

    7 publications · 256 citations

    7

    h-index

  5. BMC Public Health

    4 publications · 146 citations

    4

    h-index

1–5