Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 482

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Power and Sample Size in Multilevel Linear Models

Snijders, Tom A. B.·2005·Encyclopedia of Statistics in Behavioral Science
DOI 10.1002/0470013192.bsa492
Open this paper in CoChat — free account

Abstract

Sample size determination in multilevel designs requires attention to the fact that statistical power depends on the total sample sizes for each level. It is usually desirable to have as many units as possible at the top level of the multilevel hierarchy. Some formulas are given to obtain insight in the design aspects that are most influential for standard errors and power.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/0470013192.bsa492

Cites

12 of 12 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 12 references

Cited by

See all 482

Metadata

Authors
Snijders, T. A. B.
Venue
Encyclopedia of Statistics in Behavioral Science
Publisher
Wiley
Published
2005-04-15
DOI
10.1002/0470013192.bsa492
OpenAlex
W2153428269
Cited by
482
References
12
Type
reference entry
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Power and Sample Size in Multilevel Linear Models. https://app.cochat.ai/papers/10.1002/0470013192.bsa492
The paper
Snijders, T. A. B. (2005). Power and Sample Size in Multilevel Linear Models. Encyclopedia of Statistics in Behavioral Science. https://doi.org/10.1002/0470013192.bsa492

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.