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A framework for power analysis using a structural equation modelling procedure

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A framework for power analysis using a structural equation modelling procedure (English)

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Jeremy Miles

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1

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English

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publication date

11 December 2003

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published in

BMC Medical Research Methodology

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3

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1

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page(s)

27

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cites work

The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomised trials

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PubMed Central

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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=317297

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7 April 2017

Latent variables in psychology and the social sciences.

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Crossref

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https://api.crossref.org/works/10.1186%2F1471-2288-3-27

retrieved

21 January 2018

Asymptomatic Independence and Separability in Convariance Structure Models: Implications for Specification Error, Power, and Model Modification.

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stated in

Crossref

reference URL

https://api.crossref.org/works/10.1186%2F1471-2288-3-27

retrieved

21 January 2018

A general approach to confirmatory maximum likelihood factor analysis

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stated in

Crossref

reference URL

https://api.crossref.org/works/10.1186%2F1471-2288-3-27

retrieved

21 January 2018

Power analysis and determination of sample size for covariance structure modeling

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stated in

Crossref

reference URL

https://api.crossref.org/works/10.1186%2F1471-2288-3-27

retrieved

21 January 2018

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DOI

10.1186/1471-2288-3-27

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https://scigraph.springernature.com/pub.10.1186/1471-2288-3-27

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9 September 2019

PMC publication ID

317297

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PubMed publication ID

14670092

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ResearchGate publication ID

8964423

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(Q24805026)

A framework for power analysis using a structural equation modelling procedure

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