The DOI matches its OpenAlex record; 7 of the 7 references it cites were found in a registry or an index.
An Overview of the Logic and Rationale of Hierarchical Linear Models
Abstract
Due to the inherently hierarchical nature of organizations, data collected in organizations consist of nested entities. More specifically, individuals are nested in work groups, work groups are nested in departments, departments are nested in organizations, and organizations are nested in environments. Hierarchical linear models provide a conceptual and statistical mechanism for investigating and drawing conclusions regarding the influence of phenomena at different levels of analysis. This introductory paper: (a) discusses the logic and rationale of hierarchical linear models, (b) presents a conceptual description of the estimation strategy, and (c) using a hypothetical set of research questions, provides an overview of a typical series of multi-level models that might be investigated.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Random-Effects Models for Longitudinal Data
Laird, N. M., & Ware, J. H. (1982) · Biometrics · doi:10.2307/2529876 · Cited by 8,923
Estimating within-group interrater reliability with and without response bias
James, L. R., Demaree, R. G., & Wolf, G. (1984) · Journal of Applied Psychology · doi:10.1037/0021-9010.69.1.85 · Cited by 4,774
rwg: an assessment of within-group interrater agreement
James, L. R., Demaree, R. G., & Wolf, G. (1993) · Journal of Applied Psychology · doi:10.1037/0021-9010.78.2.306 · Cited by 2,221
Levels issues in theory development, data collection and analysis
Klein, K. J., Dansereau, F., & Hall, R. J. (1994) · The Academy of Management Review · doi:10.2307/258703 · Cited by 1,607
Parametric empirical Bayes inference: theory and applications
Morris, C. N. (1983) · Journal of the American Statistical Association · doi:10.1080/01621459.1983.10477920 · Cited by 1,448 · cited 4×
“Bryk and Raudenbush (1992) drawing on the OLS regression rule of thumb of 10 observations per predictor, mentioned that analogous rules for hierarchical linear models can be developed.”
BackgroundMethodInfluentialMANAGERIAL AND ORGANIZATIONAL FACTORS ASSOCIATED WITH COMPANY PERFORMANCE PART I
Child, J. (1974) · Journal of Management Studies · doi:10.1111/j.1467-6486.1974.tb00693.x · Cited by 536
A disagreement about within-group agreement: disentangling issues of consistency versus consensus
Kozlowski, S. W., & Hattrup, K. (1992) · Journal of Applied Psychology · doi:10.1037/0021-9010.77.2.161 · Cited by 514
Cited by
A general multilevel SEM framework for assessing multilevel mediation
Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010) · Psychological Methods · doi:10.1037/a0020141 · Cited by 3,796
On making causal claims: A review and recommendations
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010) · The Leadership Quarterly · doi:10.1016/j.leaqua.2010.10.010 · Cited by 2,441
Abusive Supervision in Work Organizations: Review, Synthesis, and Research Agenda
Tepper, B. J. (2007) · Journal of Management · doi:10.1177/0149206307300812 · Cited by 1,698
Shanock, L. R., & Eisenberger, R. (2006) · Journal of Applied Psychology · doi:10.1037/0021-9010.91.3.689 · Cited by 1,096
Interactions Within Groups and Subgroups: The Effects of Demographic Faultlines
Lau, D. C., & Murnighan, J. K. (2005) · Academy of Management Journal · doi:10.5465/amj.2005.17843943 · Cited by 831
Metadata
- Authors
- Hofmann, D. A.
- Venue
- Journal of Management
- Publisher
- SAGE Publishing
- Published
- 1997-01-01
- Volume
- 23
- Issue
- 6
- Pages
- 723-744
- ISSN
- 0149-2063 (ISSN-L)
- OpenAlex
- W2116070274
- Cited by
- 1,582
- References
- 7
- FWCI
- 10.69
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.