Parameter Invariance Testing

Parameter Invariance Testing is a methodological procedure in model fit assessment that evaluates whether the estimated parameters of a statistical model remain consistent across distinct subgroups or measurement occasions, thereby ensuring the stability and generalizability of the model’s structure under varying conditions.

70

Publications

5.4K

Citations

186

Authors

121

Institutions

Publications per year

2017–2026

23

Variants

Measurement Invariance Testing

Authors

186

  1. BD
    Bruno D. Zumbo

    University of British Columbia, Canada

    3 publications · 156 citations

    3

    h-index

  2. CD
    Chia‐Liang Dai

    University of Nevada, Las Vegas, United States

    2 publications · 108 citations

    2

    h-index

  3. CC
    Ching‐Chen Chen

    University of Nevada, Las Vegas, United States

    2 publications · 108 citations

    2

    h-index

  4. GT
    Gerard T. Kyle

    Texas A&M University, United States

    2 publications · 70 citations

    2

    h-index

  5. GB
    George B. Richardson

    University of Cincinnati, United States

    2 publications · 108 citations

    2

    h-index

1–5 of 186

Venues

  1. Educational and Psychological Measurement

    4 publications · 211 citations

    4

    h-index

  2. Measurement in Physical Education and Exercise Science

    MPEES · 3 publications · 103 citations

    3

    h-index

  3. 3

    h-index

  4. Frontiers in Psychology

    2 publications · 28 citations

    2

    h-index

  5. Review of Educational Research

    RER · 2 publications · 198 citations

    2

    h-index

1–5