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Two-step analysis of hierarchical data

Author

Listed:
  • Johannes Giesecke

    (Humboldt-University Berlin)

  • Ulrich Kohler

    (University of Potsdam)

Abstract

In this article, we describe the package twostep, a bundle of pro- grams to perform analyses of hierarchical data applying the two-step approach. We consider a two-level data setup in which “microlevel” units are nested within “macrolevel” units. One-step models (which can be fit using, for example, mixed) are the most common approach to modeling two-level data. The two-step approach is an alternative in which parameters associated with microlevel and macrolevel predictors are estimated separately for each level. It can be used as an alterna- tive to one-step models if the estimand is a cross-level interaction. We also show how the two-step approach usefully complements one-step approaches by providing exploratory data analysis, descriptive graphs, and regression diagnostics.

Suggested Citation

  • Johannes Giesecke & Ulrich Kohler, 2024. "Two-step analysis of hierarchical data," Stata Journal, StataCorp LP, vol. 24(2), pages 213-249, June.
    • Handle: RePEc:tsj:stataj:v:24:y:2024:i:2:p:213-249
    DOI: 10.1177/1536867X241257801
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    Cited by:

    1. Rhea Ravenna Sohst & Alessio Fusco & Philippe Van Kerm, 2024. "Foreign-born households’ contribution to inequality and polarization in European income distributions," LISER Working Paper Series 2024-06, Luxembourg Institute of Socio-Economic Research (LISER).

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