The DOI matches its Crossref record, with a small difference in title or year.
Dyadic Data Analysis Using Multilevel Modeling
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
For outcomes variables reported by patients and FCs, multilevel modeling (MLM) is recommended to account for the nonindependence of data within the dyad and the presence of repeated measures.
“For the outcomes variables reported by patients and FCs, multilevel modeling (MLM) is recommended to account for the nonindependence of data within the dyad and the presence of repeated measures [103].”
Citations
Cited by
Sorted by citations
Heteronormative relationship education for same-gender couples
Hatch, S. G., Rothman, K., Roddy, M. K., Dominguez, R. M., Le, Y., & Doss, B. D. (2021) · Family Process · doi:10.1111/famp.12548 · Cited by 23
Self-disclosure is associated with adrenocortical attunement between new acquaintances
Thorson, K. R., Ketay, S., Roy, A. R. K., & Welker, K. M. (2021) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2021.105323 · Cited by 3
Metadata
- Authors
- Kenny, D. A., & Kashy, D. A.
- Affiliations
- University of Connecticut (US)
- Michigan State University (US)
- Venue
- Handbook of Advanced Multilevel Analysis
- Publisher
- Routledge
- Published
- 2015-02-17
- OpenAlex
- W2464966491
- Cited by
- 61
- References
- 0
- Citations by year
- 2023: 3 · 2022: 4 · 2021: 7 · 2020: 6 · 2019: 8 · 2018: 7 · 2017: 5 · 2016: 2 · 2015: 4
- FWCI
- 21.14
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Psychology › Social Psychology › Attachment and Relationship Dynamics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- dyadic data, multilevel modeling, dyadic analysis
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 ›
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