ArticleSocial science research2015
The power of a paired t-test with a covariate.
Article in Social science research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
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- Is the Bland-Altman plot method useful without inferences for accuracy, precision, and agreement?Revista de saude publica · 2024Article
- Letter: "Motor and functional outcome of selective dorsal rhizotomy in children with spastic diplegia at 12 and 24 months of follow-up".Acta neurochirurgica · 2022Article
- The impact of COVID-19 on higher education building energy use and implications for future education building energy studies.Energy and buildings · 2021Article
- Abundance, distribution, and characteristics of microplastics in coastal surface waters of the Colombian Caribbean and Pacific.Environmental science and pollution research international · 2021Article
- An Open Trial of Metacognitive Remediation Therapy and Pharmacotherapy to Promote Smoking Cessation among Individuals with Psychotic-Spectrum Disorders.Journal of smoking cessation · 2021Article
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- Effectiveness of a Multimodal Digital Psychotherapy Platform for Adult Depression: A Naturalistic Feasibility Study.JMIR mHealth and uHealth · 2019Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Many researchers employ the paired t-test to evaluate the mean difference between matched data points. Unfortunately, in many cases this test in inefficient. This paper reviews how to increase the precision of this test through using the mean centered independent variable x, which is familiar to researchers that use analysis of covariance (ANCOVA). We add to the literature by demonstrating how to employ these gains in efficiency as a factor for use in finding the statistical power of the test. The key parameters for this factor are the correlation between the two measures and the variance ratio of the dependent measure on the predictor. The paper then demonstrates how to compute the gains in efficiency a priori to amend the power computations for the traditional paired t-test. We include an example analysis from a recent intervention, Families Preparing the New Generation (Familias Preparando la Nueva Generación). Finally, we conclude with an analysis of extant data to derive reasonable parameter values.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.