Small numbers are an opportunity, not a problem

Detalhes bibliográficos
Autor(a) principal: Leppink, Jimmie
Data de Publicação: 2021
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Medica (Porto Alegre. Online)
Texto Completo: https://revistaseletronicas.pucrs.br/scientiamedica/article/view/40128
Resumo: Aims: outcomes of research in education and training are partly a function of the context in which that study takes place, the questions we ask, and what is feasible. Many questions are about learning, which involves repeated measurements in a particular time window, and the practical context is usually such that offering an intervention to some but not to all learners does not make sense or is unethical. For quality assurance and other purposes, education and training centers may have very locally oriented questions that they seek to answer, such as whether an intervention can be considered effective in their context of small numbers of learners. While the rationale behind the design and outcomes of this kind of studies may be of interest to a much wider community, for example to study the transferability of findings to other contexts, people are often discouraged to report on the outcomes of such studies at conferences or in educational research journals. The aim of this paper is to counter that discouragement and instead encourage people to see small numbers as an opportunity instead of as a problem.Method: a worked example of a parametric and a non-parametric method for this type of situation, using simulated data in the zero-cost Open Source statistical program R version 4.0.5.Results: contrary to the non-parametric method, the parametric method can provide estimates of intervention effectiveness for the individual participant, account for trends in different phases of a study. However, the non-parametric method provides a solution in several situations where the parametric method should be used.Conclusion: Given the costs of research, the lessons to be learned from research, and statistical methods available, small numbers should be considered an opportunity, not a problem.
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spelling Small numbers are an opportunity, not a problemNúmeros pequenos são uma oportunidade, não um problemamixed modelpercentage of all non-overlapping data bayessingle case designsingle case experimental designtime seriesmodelo mistoporcentagem de todos os dados bayes não sobrepostosprojeto de caso únicoprojeto experimental de caso únicoséries temporaisAims: outcomes of research in education and training are partly a function of the context in which that study takes place, the questions we ask, and what is feasible. Many questions are about learning, which involves repeated measurements in a particular time window, and the practical context is usually such that offering an intervention to some but not to all learners does not make sense or is unethical. For quality assurance and other purposes, education and training centers may have very locally oriented questions that they seek to answer, such as whether an intervention can be considered effective in their context of small numbers of learners. While the rationale behind the design and outcomes of this kind of studies may be of interest to a much wider community, for example to study the transferability of findings to other contexts, people are often discouraged to report on the outcomes of such studies at conferences or in educational research journals. The aim of this paper is to counter that discouragement and instead encourage people to see small numbers as an opportunity instead of as a problem.Method: a worked example of a parametric and a non-parametric method for this type of situation, using simulated data in the zero-cost Open Source statistical program R version 4.0.5.Results: contrary to the non-parametric method, the parametric method can provide estimates of intervention effectiveness for the individual participant, account for trends in different phases of a study. However, the non-parametric method provides a solution in several situations where the parametric method should be used.Conclusion: Given the costs of research, the lessons to be learned from research, and statistical methods available, small numbers should be considered an opportunity, not a problem.Objetivo: os resultados da pesquisa em educação e treinamento são, em parte, uma função do contexto em que esse estudo ocorre, das perguntas que fazemos e do que é viável. Muitas perguntas são sobre a aprendizagem, que envolve medições repetidas em uma janela de tempo específica, e o contexto prático, geralmente, é tal, que oferecer uma intervenção a alguns, mas não a todos os alunos, não faz sentido ou é antiético. Para garantia de qualidade e outros propósitos, os centros de educação e treinamento podem ter perguntas orientadas localmente que procuram responder, como, por exemplo, se uma intervenção pode ser considerada eficaz em seu contexto de pequeno número de alunos. Embora a justificativa por trás do projeto e dos resultados deste tipo de estudos possa ser do interesse de uma comunidade muito mais ampla, por exemplo, para estudar a possibilidade de transferência de resultados para outros contextos, as pessoas são frequentemente desencorajadas a relatar os resultados de tais estudos em conferências ou em revistas de pesquisa educacional. O objetivo deste artigo é combater esse desânimo e, em vez disso, incentivar as pessoas a verem os pequenos números como uma oportunidade em vez de um problema.Método: realizado um exemplo de método paramétrico e não paramétrico para este tipo de situação, utilizando dados simulados no programa estatístico Open Source R versão 4.0.5 de custo zero.Resultados: ao contrário do método não paramétrico, o método paramétrico pode fornecer estimativas da eficácia da intervenção para o participante individual, levando em conta as tendências em diferentes fases de um estudo. No entanto, o método não paramétrico fornece uma solução em várias situações, onde o método paramétrico deve ser usado.Conclusão: dados os custos da pesquisa, as lições a serem aprendidas com a pesquisa e os métodos estatísticos disponíveis, pequenos números devem ser considerados uma oportunidade, não um problema.Editora da PUCRS - ediPUCRS2021-06-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistaseletronicas.pucrs.br/scientiamedica/article/view/4012810.15448/1980-6108.2021.1.40128Scientia Medica; Vol. 31 No. 1 (2021): Single Volume; e40128Scientia Medica; v. 31 n. 1 (2021): Volume Único; e401281980-61081806-556210.15448/1980-6108.2021.1reponame:Scientia Medica (Porto Alegre. Online)instname:Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)instacron:PUC_RSenghttps://revistaseletronicas.pucrs.br/scientiamedica/article/view/40128/26901Copyright (c) 2021 Scientia Medicahttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessLeppink, Jimmie2022-01-25T17:01:59Zoai:ojs.revistaseletronicas.pucrs.br:article/40128Revistahttps://revistaseletronicas.pucrs.br/scientiamedica/PUBhttps://revistaseletronicas.pucrs.br/scientiamedica/oaiscientiamedica@pucrs.br || editora.periodicos@pucrs.br1980-61081806-5562opendoar:2022-01-25T17:01:59Scientia Medica (Porto Alegre. Online) - Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)false
dc.title.none.fl_str_mv Small numbers are an opportunity, not a problem
Números pequenos são uma oportunidade, não um problema
title Small numbers are an opportunity, not a problem
spellingShingle Small numbers are an opportunity, not a problem
Leppink, Jimmie
mixed model
percentage of all non-overlapping data bayes
single case design
single case experimental design
time series
modelo misto
porcentagem de todos os dados bayes não sobrepostos
projeto de caso único
projeto experimental de caso único
séries temporais
title_short Small numbers are an opportunity, not a problem
title_full Small numbers are an opportunity, not a problem
title_fullStr Small numbers are an opportunity, not a problem
title_full_unstemmed Small numbers are an opportunity, not a problem
title_sort Small numbers are an opportunity, not a problem
author Leppink, Jimmie
author_facet Leppink, Jimmie
author_role author
dc.contributor.author.fl_str_mv Leppink, Jimmie
dc.subject.por.fl_str_mv mixed model
percentage of all non-overlapping data bayes
single case design
single case experimental design
time series
modelo misto
porcentagem de todos os dados bayes não sobrepostos
projeto de caso único
projeto experimental de caso único
séries temporais
topic mixed model
percentage of all non-overlapping data bayes
single case design
single case experimental design
time series
modelo misto
porcentagem de todos os dados bayes não sobrepostos
projeto de caso único
projeto experimental de caso único
séries temporais
description Aims: outcomes of research in education and training are partly a function of the context in which that study takes place, the questions we ask, and what is feasible. Many questions are about learning, which involves repeated measurements in a particular time window, and the practical context is usually such that offering an intervention to some but not to all learners does not make sense or is unethical. For quality assurance and other purposes, education and training centers may have very locally oriented questions that they seek to answer, such as whether an intervention can be considered effective in their context of small numbers of learners. While the rationale behind the design and outcomes of this kind of studies may be of interest to a much wider community, for example to study the transferability of findings to other contexts, people are often discouraged to report on the outcomes of such studies at conferences or in educational research journals. The aim of this paper is to counter that discouragement and instead encourage people to see small numbers as an opportunity instead of as a problem.Method: a worked example of a parametric and a non-parametric method for this type of situation, using simulated data in the zero-cost Open Source statistical program R version 4.0.5.Results: contrary to the non-parametric method, the parametric method can provide estimates of intervention effectiveness for the individual participant, account for trends in different phases of a study. However, the non-parametric method provides a solution in several situations where the parametric method should be used.Conclusion: Given the costs of research, the lessons to be learned from research, and statistical methods available, small numbers should be considered an opportunity, not a problem.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-30
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistaseletronicas.pucrs.br/scientiamedica/article/view/40128
10.15448/1980-6108.2021.1.40128
url https://revistaseletronicas.pucrs.br/scientiamedica/article/view/40128
identifier_str_mv 10.15448/1980-6108.2021.1.40128
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistaseletronicas.pucrs.br/scientiamedica/article/view/40128/26901
dc.rights.driver.fl_str_mv Copyright (c) 2021 Scientia Medica
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Scientia Medica
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da PUCRS - ediPUCRS
publisher.none.fl_str_mv Editora da PUCRS - ediPUCRS
dc.source.none.fl_str_mv Scientia Medica; Vol. 31 No. 1 (2021): Single Volume; e40128
Scientia Medica; v. 31 n. 1 (2021): Volume Único; e40128
1980-6108
1806-5562
10.15448/1980-6108.2021.1
reponame:Scientia Medica (Porto Alegre. Online)
instname:Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)
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instname_str Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)
instacron_str PUC_RS
institution PUC_RS
reponame_str Scientia Medica (Porto Alegre. Online)
collection Scientia Medica (Porto Alegre. Online)
repository.name.fl_str_mv Scientia Medica (Porto Alegre. Online) - Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)
repository.mail.fl_str_mv scientiamedica@pucrs.br || editora.periodicos@pucrs.br
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