Space-time Permutation Models

Space-Time Permutation Models is a statistical method in spatial cluster analysis that identifies space-time disease clusters by permuting case times within locations to assess the significance of observed spatiotemporal patterns while adjusting for purely spatial and purely temporal trends.

37

Publications

2.7K

Citations

189

Authors

114

Institutions

Publications per year

2017–2026

16

Authors

189

  1. CS
    Chalutwan Sansamur

    Chiang Mai University, Thailand

    3 publications · 115 citations

    3

    h-index

  2. DL
    David L. Pearl

    University of Guelph, Canada

    3 publications · 72 citations

    3

    h-index

  3. OA
    Orapun Arjkumpa

    Chiang Mai University, Thailand

    3 publications · 115 citations

    3

    h-index

  4. MK
    Martin Kulldorff

    Harvard University, United States

    3 publications · 1.2K citations

    3

    h-index

  5. VP
    Veerasak Punyapornwithaya

    Chiang Mai University, Thailand

    3 publications · 115 citations

    3

    h-index

1–5 of 189

Venues

  1. PLoS ONE

    6 publications · 310 citations

    6

    h-index

  2. Frontiers in Veterinary Science

    2 publications · 95 citations

    2

    h-index

  3. Pathogens

    2 publications · 84 citations

    2

    h-index

  4. BMC Veterinary Research

    2 publications · 36 citations

    2

    h-index

  5. Parasites & Vectors

    2 publications · 59 citations

    2

    h-index

1–5