Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia

Autores:: Altay, Yasin
Koskan, Ozgur
Koknaroglu, Hayati

Tipo de recurso:: Article of journal

Fecha de publicación:: 2022

Institución:: Universidad de Córdoba

Repositorio:: Repositorio Institucional Unicórdoba

Idioma:: spa

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dc.title.spa.fl_str_mv	Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia
dc.title.translated.eng.fl_str_mv	Determination of minimum number of animals in comparing treatment means by power analysis
title	Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia
spellingShingle	Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia Effect size minimum number of animals sample size power analysis simulation Tamaño del efecto Número mínimo de animales Tamaño de la muestra Análisis de potencia simulación
title_short	Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia
title_full	Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia
title_fullStr	Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia
title_full_unstemmed	Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia
title_sort	Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia
dc.creator.fl_str_mv	Altay, Yasin Koskan, Ozgur Koknaroglu, Hayati
dc.contributor.author.spa.fl_str_mv	Altay, Yasin Koskan, Ozgur Koknaroglu, Hayati
dc.subject.eng.fl_str_mv	Effect size minimum number of animals sample size power analysis simulation
topic	Effect size minimum number of animals sample size power analysis simulation Tamaño del efecto Número mínimo de animales Tamaño de la muestra Análisis de potencia simulación
dc.subject.spa.fl_str_mv	Tamaño del efecto Número mínimo de animales Tamaño de la muestra Análisis de potencia simulación
publishDate	2022
dc.date.accessioned.none.fl_str_mv	2022-07-31 22:38:42 2022-08-01T09:36:32Z
dc.date.available.none.fl_str_mv	2022-07-31 22:38:42 2022-08-01T09:36:32Z
dc.date.issued.none.fl_str_mv	2022-07-31
dc.type.spa.fl_str_mv	Artículo de revista
dc.type.eng.fl_str_mv	Journal article
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dc.relation.references.spa.fl_str_mv	Akobeng AK. Understanding type I and type II errors, statistical power and sample size. Acta Paediatrica. 2016; 105(6):605-609. https://doi.org/10.1111/apa.13384 Greenland S, Senn SJ, Rothman KJ, Carlin JB, Poole, C, Goodman SN, Altman DG. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016; 31(4):337-350. https://doi.org/10.1007/s10654-016-0149-3 Cohen J. Statistical power analysis: Current Directions in Psychological Science 1992; 1(3):98-101. https://doi.org/10.1111/1467-8721.ep10768783 Wilcox RR. ANOVA: A paradigm for low power and misleading measures of effect size?. Rev Educ Res. 1995; 65(1):51-77. https://doi.org/10.3102/00346543065001051 Kelley K, Rausch, JR. Sample size planning for the standardized mean difference: Accuracy in parameter estimation via narrow confidence intervals. Psychol Methods. 2006; 11(4):363–385. https://doi.org/10.1037/1082-989X.11.4.363 Houle TT, Penzien DB, Houle CK. Statistical power and sample size estimation for headache research: An overview and power calculation tools. Headache. 2005; 45(5):414-418. https://doi.org/10.1111/j.1526-4610.2005.05092.x Mascha EJ, Vetter TR. Significance, errors, power, and sample size: the blocking and tackling of statistics. Anesth Analg. 2018; 126(2):691-698. https://doi.org/10.1213/ANE.0000000000002741 Aslan E, Koşkan Ö, Altay Y. Determination of the Sample Size on Different Independent K Group Comparisons by Power Analysis. Turk Tarim Arast Derg. 2021; 8(1):34-41. https://doi.org/10.19159/tutad.792694 Szucs D, Ioannidis JP. Sample size evolution in neuroimaging research: An evaluation of highly-cited studies (1990–2012) and of latest practices (2017–2018) in high-impact journals. NeuroImage. 2020; 221:117-164. https://doi.org/10.1016/j.neuroimage.2020.117164 Murphy KR. Myors B. Statistical power analysis: A simple and general model for traditional and modern hypothesis tests. Second Edition (2rd ed.). Mahwah, New Jersey, USA: Lawrence Erlbaum Associates Publishers; 2004. Lane SP, Hennes EP. Power struggles: Estimating sample size for multilevel relationships research. J Soc Pers Relat. 2018; 35(1):7-31. https://doi.org/10.1177/0265407517710342 Peterman RM. Statistical power analysis can improve fisheries research and management. Can J Fish Aquat Sci. 1990; 47(1):2–15. https://doi.org/10.1139/f90-001 Fairweather PG. Statistical power and design requirements for environmental monitoring. Mar Freshw Res. 1991; 42(5):555–567. https://doi.org/10.1071/MF9910555 Muller KE, Benignus VA. Increasing scientific power with statistical power. Neurotoxicol Teratol. 1992; 14(3):211–219. https://doi.org/10.1016/0892-0362(92)90019-7 Taylor BL, Gerrodette T. The uses of statistical power in conservation biology: the vaquita and northern spotted owl. Conserv Biol Ser. 1993; 7(3):489–500. https://doi.org/10.1046/j.1523-1739.1993.07030489.x Searcy-Bernal R. Statistical power and aquacultural research. Aquaculture. 1994; 127(4):371–388. https://doi.org/10.1016/0044-8486(94)90239-9 Thomas L, Juanes F. The importance of statistical power analysis: an example from animal behaviour. Anim. Behav. 1996; 52(4):856–859. https://doi.org/10.1006/anbe.1996.0232 Thomas L, Retrospective power analysis. Conservation Biology. Conservation Biology. 1997; 11(1):276-280. https://www.jstor.org/stable/2387304 Pinu FR, Beale DJ, Paten AM, Kouremenos K, Swarup S, Schirra HJ, Wishart D. Systems biology and multi-omics integration: viewpoints from the metabolomics research community. Metabolites. 2019; 9(4):76. https://doi.org/10.3390/metabo9040076 Hoenig JM, Heisey DM. The abuse of power: the pervasive fallacy of power calculations for data analysis. Am Stat. 2001; 55(1):19-24. https://doi.org/10.1198/000313001300339897 Faul F, Erdfelder E, Lang AG, Buchner AG. Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007; 39(2):175-191. https://doi.org/10.3758/BF03193146 La Rosa PS, Brooks JP, Deych E, Boone EL, Edwards DJ, Wang Q, Sodergren E, Weinstock G, Shannon WD. Hypothesis testing and power calculations for taxonomic-based human microbiome data. PloS One. 2012; 7(12):e52078. https://doi.org/10.1371/journal.pone.0052078 Fanelli D. Do pressures to publish increase scientists’ bias? An empirical support from US States Data. PloS One. 2010; 5(4):e10271. https://doi.org/10.1371/journal.pone.0010271 Abt G, Boreham C, Davison G, Jackson R, Nevill A, Wallacea E, Williamsa M. Power, precision, and sample size estimation in sport and exercise science research. J Sports Sci. 2020; 38(17):1993-1935. https://10.1080/02640414.2020.1776002 Lewis KP. Statistical power, sample sizes, and the software to calculate them easily. BioScience. 2006; 56(7):607-612. https://doi.org/10.1641/0006-3568(2006)56[607:SPSSAT]2.0.CO;2 Zar JH. Biostatistical Analysis: Pearson New International Edition. New Jersey, NJ, USA: Pearson Higher Edition; 2013. Hartley HO. The maximum F-ratio as a short-cut test for heterogeneity of variance. Biometrika. 1950; 37(3/4):308-312. https://doi.org/10.2307/2332383 Pearson ES, Hartley HO. Charts of the power function for analysis of variance tests, derived from the non-central F-distribution. Biometrika. 1951; 38(1/2):112-130. https://doi.org/10.2307/2332321 Başpınar E. Gürbüz F, The power of the test in comparing samples of different sample sizes taken from binary combinations of Normal, Beta, Gamma (Chi-square) and Weibull distributions. J Agric Sci. 2000; 6(1):116-127. https://doi.org/10.1501/Tarimbil_0000000940 Lenth RV. Statistical power calculations. J Anim Sci. 2007; 85(13):24-29. https://doi.org/10.2527/jas.2006-449 Başpınar E, Type I error and power of the test obtained by applying Student’s t, Welch and sorted t-tests on two samples of different sample sizes taken from normal populations with different variance ratios. J Anim Sci. 2001; 7(1):151-157. https://doi.org/10.1501/Tarimbil_0000000271 Koşkan Ö, Gürbüz F. Resampling approach and power of t-test and comparison of type I error. J Anim Prod. 2008; 49(1):29-37. https://dergipark.org.tr/en/pub/hayuretim/issue/7617/99817 Kalaycioğlu O, Akhanli SE. The importance and main principles of power analysis in health research: Application examples on medical case studies. Turk J Public Health. 2020;. 18(1):103-112. https://doi.org/10.20518/tjph.602400 Mewhort, DJ, A comparison of the randomization test with the F test when error is skewed. Behav Res Methods. 2005; 37(3):426-435. https://doi.org/10.3758/BF03192711
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dc.relation.citationedition.spa.fl_str_mv	Núm. 2 , Año 2022 : Revista MVZ Córdoba Volumen 27(2) Mayo-Agosto 2022
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dc.rights.spa.fl_str_mv	Yasin Altay, Ozgur Koskan, Hayati Koknaroglu - 2022
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spelling	Altay, Yasinfdf0dba9-5b14-417e-9e08-455030a7a89d-1Koskan, Ozgurfc2071d9-9b42-4350-8e91-ac2b01f002d9-1Koknaroglu, Hayati030cc5a8-b392-4675-9ae4-2a89b64a9f8b-12022-07-31 22:38:422022-08-01T09:36:32Z2022-07-31 22:38:422022-08-01T09:36:32Z2022-07-310122-0268https://repositorio.unicordoba.edu.co/handle/ucordoba/621610.21897/rmvz.2572https://doi.org/10.21897/rmvz.25721909-0544application/pdfapplication/pdfaudio/mpegaudio/mpegspaUniversidad de CórdobaYasin Altay, Ozgur Koskan, Hayati Koknaroglu - 2022https://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.http://purl.org/coar/access_right/c_abf2https://revistamvz.unicordoba.edu.co/article/view/2572Effect sizeminimum number of animalssample sizepower analysissimulationTamaño del efectoNúmero mínimo de animalesTamaño de la muestraAnálisis de potenciasimulaciónDeterminación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potenciaDetermination of minimum number of animals in comparing treatment means by power analysisArtículo de revistaJournal articleinfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/publishedVersionTexthttp://purl.org/redcol/resource_type/ARTREFhttp://purl.org/coar/version/c_970fb48d4fbd8a85Akobeng AK. Understanding type I and type II errors, statistical power and sample size. Acta Paediatrica. 2016; 105(6):605-609. https://doi.org/10.1111/apa.13384Greenland S, Senn SJ, Rothman KJ, Carlin JB, Poole, C, Goodman SN, Altman DG. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016; 31(4):337-350. https://doi.org/10.1007/s10654-016-0149-3Cohen J. Statistical power analysis: Current Directions in Psychological Science 1992; 1(3):98-101. https://doi.org/10.1111/1467-8721.ep10768783Wilcox RR. ANOVA: A paradigm for low power and misleading measures of effect size?. Rev Educ Res. 1995; 65(1):51-77. https://doi.org/10.3102/00346543065001051Kelley K, Rausch, JR. Sample size planning for the standardized mean difference: Accuracy in parameter estimation via narrow confidence intervals. Psychol Methods. 2006; 11(4):363–385. https://doi.org/10.1037/1082-989X.11.4.363Houle TT, Penzien DB, Houle CK. Statistical power and sample size estimation for headache research: An overview and power calculation tools. Headache. 2005; 45(5):414-418. https://doi.org/10.1111/j.1526-4610.2005.05092.xMascha EJ, Vetter TR. Significance, errors, power, and sample size: the blocking and tackling of statistics. Anesth Analg. 2018; 126(2):691-698. https://doi.org/10.1213/ANE.0000000000002741Aslan E, Koşkan Ö, Altay Y. Determination of the Sample Size on Different Independent K Group Comparisons by Power Analysis. Turk Tarim Arast Derg. 2021; 8(1):34-41. https://doi.org/10.19159/tutad.792694Szucs D, Ioannidis JP. Sample size evolution in neuroimaging research: An evaluation of highly-cited studies (1990–2012) and of latest practices (2017–2018) in high-impact journals. NeuroImage. 2020; 221:117-164. https://doi.org/10.1016/j.neuroimage.2020.117164Murphy KR. Myors B. Statistical power analysis: A simple and general model for traditional and modern hypothesis tests. Second Edition (2rd ed.). Mahwah, New Jersey, USA: Lawrence Erlbaum Associates Publishers; 2004.Lane SP, Hennes EP. Power struggles: Estimating sample size for multilevel relationships research. J Soc Pers Relat. 2018; 35(1):7-31. https://doi.org/10.1177/0265407517710342Peterman RM. Statistical power analysis can improve fisheries research and management. Can J Fish Aquat Sci. 1990; 47(1):2–15. https://doi.org/10.1139/f90-001Fairweather PG. Statistical power and design requirements for environmental monitoring. Mar Freshw Res. 1991; 42(5):555–567. https://doi.org/10.1071/MF9910555Muller KE, Benignus VA. Increasing scientific power with statistical power. Neurotoxicol Teratol. 1992; 14(3):211–219. https://doi.org/10.1016/0892-0362(92)90019-7Taylor BL, Gerrodette T. The uses of statistical power in conservation biology: the vaquita and northern spotted owl. Conserv Biol Ser. 1993; 7(3):489–500. https://doi.org/10.1046/j.1523-1739.1993.07030489.xSearcy-Bernal R. Statistical power and aquacultural research. Aquaculture. 1994; 127(4):371–388. https://doi.org/10.1016/0044-8486(94)90239-9Thomas L, Juanes F. The importance of statistical power analysis: an example from animal behaviour. Anim. Behav. 1996; 52(4):856–859. https://doi.org/10.1006/anbe.1996.0232Thomas L, Retrospective power analysis. Conservation Biology. Conservation Biology. 1997; 11(1):276-280. https://www.jstor.org/stable/2387304Pinu FR, Beale DJ, Paten AM, Kouremenos K, Swarup S, Schirra HJ, Wishart D. Systems biology and multi-omics integration: viewpoints from the metabolomics research community. Metabolites. 2019; 9(4):76. https://doi.org/10.3390/metabo9040076Hoenig JM, Heisey DM. The abuse of power: the pervasive fallacy of power calculations for data analysis. Am Stat. 2001; 55(1):19-24. https://doi.org/10.1198/000313001300339897Faul F, Erdfelder E, Lang AG, Buchner AG. Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007; 39(2):175-191. https://doi.org/10.3758/BF03193146La Rosa PS, Brooks JP, Deych E, Boone EL, Edwards DJ, Wang Q, Sodergren E, Weinstock G, Shannon WD. Hypothesis testing and power calculations for taxonomic-based human microbiome data. PloS One. 2012; 7(12):e52078. https://doi.org/10.1371/journal.pone.0052078Fanelli D. Do pressures to publish increase scientists’ bias? An empirical support from US States Data. PloS One. 2010; 5(4):e10271. https://doi.org/10.1371/journal.pone.0010271Abt G, Boreham C, Davison G, Jackson R, Nevill A, Wallacea E, Williamsa M. Power, precision, and sample size estimation in sport and exercise science research. J Sports Sci. 2020; 38(17):1993-1935. https://10.1080/02640414.2020.1776002Lewis KP. Statistical power, sample sizes, and the software to calculate them easily. BioScience. 2006; 56(7):607-612. https://doi.org/10.1641/0006-3568(2006)56[607:SPSSAT]2.0.CO;2Zar JH. Biostatistical Analysis: Pearson New International Edition. New Jersey, NJ, USA: Pearson Higher Edition; 2013.Hartley HO. The maximum F-ratio as a short-cut test for heterogeneity of variance. Biometrika. 1950; 37(3/4):308-312. https://doi.org/10.2307/2332383Pearson ES, Hartley HO. Charts of the power function for analysis of variance tests, derived from the non-central F-distribution. Biometrika. 1951; 38(1/2):112-130. https://doi.org/10.2307/2332321Başpınar E. Gürbüz F, The power of the test in comparing samples of different sample sizes taken from binary combinations of Normal, Beta, Gamma (Chi-square) and Weibull distributions. J Agric Sci. 2000; 6(1):116-127. https://doi.org/10.1501/Tarimbil_0000000940Lenth RV. Statistical power calculations. J Anim Sci. 2007; 85(13):24-29. https://doi.org/10.2527/jas.2006-449Başpınar E, Type I error and power of the test obtained by applying Student’s t, Welch and sorted t-tests on two samples of different sample sizes taken from normal populations with different variance ratios. J Anim Sci. 2001; 7(1):151-157. https://doi.org/10.1501/Tarimbil_0000000271Koşkan Ö, Gürbüz F. Resampling approach and power of t-test and comparison of type I error. J Anim Prod. 2008; 49(1):29-37. https://dergipark.org.tr/en/pub/hayuretim/issue/7617/99817Kalaycioğlu O, Akhanli SE. The importance and main principles of power analysis in health research: Application examples on medical case studies. Turk J Public Health. 2020;. 18(1):103-112. https://doi.org/10.20518/tjph.602400Mewhort, DJ, A comparison of the randomization test with the F test when error is skewed. Behav Res Methods. 2005; 37(3):426-435. https://doi.org/10.3758/BF03192711https://revistamvz.unicordoba.edu.co/article/download/2572/4026https://revistamvz.unicordoba.edu.co/article/download/2572/4027https://revistamvz.unicordoba.edu.co/article/download/2572/4028https://revistamvz.unicordoba.edu.co/article/download/2572/4029Núm. 2 , Año 2022 : Revista MVZ Córdoba Volumen 27(2) Mayo-Agosto 2022e25722e257227Revista MVZ CórdobaPublicationOREORE.xmltext/xml3218https://repositorio.unicordoba.edu.co/bitstreams/dc1cc32b-a0e4-4d62-a0c8-4bbfffdc41c2/download8a50faeb77a827ac80373b98bf9df832MD51ucordoba/6216oai:repositorio.unicordoba.edu.co:ucordoba/62162023-10-06 00:46:24.881https://creativecommons.org/licenses/by-nc-sa/4.0Yasin Altay, Ozgur Koskan, Hayati Koknaroglu - 2022metadata.onlyhttps://repositorio.unicordoba.edu.coRepositorio Universidad de Córdobabdigital@metabiblioteca.com

Determinación del número mínimo de animales al comparar las medias de tratamiento mediante análisis de potencia

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