Absence Data Quality

Absence Data Quality is a construct that denotes the degree to which recorded absenteeism data conforms to essential criteria such as accuracy, completeness, consistency, timeliness, and validity, thereby enabling reliable analysis and decision-making within the context of absenteeism surveillance.

12

Publications

2.7K

Citations

33

Authors

22

Institutions

Publications per year

2017–2026

3

Authors

33

  1. AH
    Alexandre H. Hirzel

    University of Lausanne, Switzerland

    2 publications · 1.6K citations

    2

    h-index

  2. DC
    Daniel Chessel

    Université Claude Bernard Lyon 1, France

    2 publications · 1.6K citations

    2

    h-index

  3. JH
    Jean Hausser

    University of Lausanne, Switzerland

    2 publications · 1.6K citations

    2

    h-index

  4. NP
    Nicolas Perrin

    University of Lausanne, Switzerland

    2 publications · 1.6K citations

    2

    h-index

  5. QG
    Qinghua Guo

    Chinese Academy of Sciences, China

    1 publications · 44 citations

    1

    h-index

1–5 of 33

Venues

  1. Journal of Applied Psychology

    2 publications · 274 citations

    2

    h-index

  2. Ecology

    2 publications · 1.6K citations

    2

    h-index

  3. Biodiversity Informatics

    1 publications · 131 citations

    1

    h-index

  4. CATENA

    1 publications · 205 citations

    1

    h-index

  5. Ecological Modelling

    1 publications · 270 citations

    1

    h-index

1–5