Administrative Data Limitations

Administrative Data Limitations is a methodological construct that refers to the inherent constraints and biases in institutionally generated records, distinguished by their impact on the accurate identification and measurement of hidden populations such as those experiencing hidden homelessness.

45

Publications

1.6K

Citations

144

Authors

73

Institutions

Publications per year

2017–2026

17

Authors

144

  1. RM
    Rigissa Megalokonomou

    The University of Queensland, Australia

    2 publications · 77 citations

    2

    h-index

  2. JK
    Joseph Keawe‘aimoku Kaholokula

    University of Hawaiʻi at Mānoa, United States

    2 publications · 45 citations

    2

    h-index

  3. SV
    Sela V. Panapasa

    University of Michigan, United States

    2 publications · 45 citations

    2

    h-index

  4. CY
    Constantine Yannelis

    University of Chicago, United States

    2 publications · 77 citations

    2

    h-index

  5. MD
    Michael Dinerstein

    University of Chicago, United States

    2 publications · 77 citations

    2

    h-index

1–5 of 144

Venues

  1. SSRN Electronic Journal

    Repository · 3 publications · 86 citations

    3

    h-index

  2. PubMed

    Repository · 3 publications · 137 citations

    3

    h-index

  3. PLoS ONE

    2 publications · 36 citations

    2

    h-index

  4. Journal of Public Health

    1 publications · 34 citations

    1

    h-index

  5. Applied Nursing Research

    ANR · 1 publications · 13 citations

    1

    h-index

1–5