SAMPLE SIZE REQUIREMENT TO SHOW THE EQUIVALENCE OF TWO TREATMENTS IN A PARALELL DESIGN
The comparison of two treatments is often formulated on the basis of contrasting hypothesis of the form Ho: m1 = m2 against Ha: m1 ¹ m2 (null and alternative hipothesis respectively), where m1 and m2 are the population means of each treatment. This formulation of the problem is convenient when the aim is to demonstrate the truth of the alternative hypothesis, but it is not when the interest is to prove the equivalence of both treatments. For a bioequivalence study, Westlake (1988) developed a procedure to show the equivalence of two treatments for a crossover design. The aim of this paper is to adapt that procedure for parallel designs, including the sample size formula. The main advantage of this procedure is that it provides an explicit expression for the sample size for given values of a and b. Its disadvantages are that the real value of the significance level is strictly less than the nominal value of a, and that it requires that both samples come from normal distributions with equal variances.
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Colegio de Postgraduados
1996
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oai:ojs.pkp.sfu.ca:article13852020-05-14T05:43:59Z SAMPLE SIZE REQUIREMENT TO SHOW THE EQUIVALENCE OF TWO TREATMENTS IN A PARALELL DESIGN TAMAÑO DE MUESTRA PARA DEMOSTRAR LA EQUIVALENCIA DE DOS TRATAMIENTOS EN UN DISEÑO EXPERIMENTAL EN PARALELO Sotres-Ramos, David Bioequivalence sample size experimental designs Bioequivalencia tamaño de muestra diseños experimentales The comparison of two treatments is often formulated on the basis of contrasting hypothesis of the form Ho: m1 = m2 against Ha: m1 ¹ m2 (null and alternative hipothesis respectively), where m1 and m2 are the population means of each treatment. This formulation of the problem is convenient when the aim is to demonstrate the truth of the alternative hypothesis, but it is not when the interest is to prove the equivalence of both treatments. For a bioequivalence study, Westlake (1988) developed a procedure to show the equivalence of two treatments for a crossover design. The aim of this paper is to adapt that procedure for parallel designs, including the sample size formula. The main advantage of this procedure is that it provides an explicit expression for the sample size for given values of a and b. Its disadvantages are that the real value of the significance level is strictly less than the nominal value of a, and that it requires that both samples come from normal distributions with equal variances. Usualmente la comparación de dos tratamientos se formula en términos del contraste de dos hipótesis (nula y alternativa, respectivamente) que tienen la forma Ho: m1 = m2 contra Ha: m1 ¹ m2; donde m1 y m2 representan las medias poblaciones de los dos tratamientos. Esto es adecuado cuando se evalúa la veracidad de la hipótesis alternativa, pero no cuando el interés es probar la equivalencia de los dos tratamientos. El objetivo de este trabajo fue adaptar el procedimiento que Westlake (1988) propuso para demostrar la equivalencia de dos tratamientos ensayados de acuerdo con un diseño experimental cruzado, al caso de estudios en paralelo, incluyendo la fórmula para calcular el tamaño de muestra requerido. La principal ventaja de este procedimiento es que proporciona una expresión explícita del tamaño de muestra para valores prefijados de a y b. Entre sus desventajas destacan que el nivel de significancia real es estrictamente menor al valor nominal de a y que se requiere que las muestras provengan de distribuciones normales con varianzas iguales. Colegio de Postgraduados 1996-09-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Artículo revisado por pares application/pdf https://www.agrociencia-colpos.org/index.php/agrociencia/article/view/1385 Agrociencia; Vol. 30 No. 3 (1996): 1996-jul-sep; 383-386 Agrociencia; Vol. 30 Núm. 3 (1996): 1996-jul-sep; 383-386 2521-9766 1405-3195 spa https://www.agrociencia-colpos.org/index.php/agrociencia/article/view/1385/1385 |
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| language |
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| author |
Sotres-Ramos, David |
| spellingShingle |
Sotres-Ramos, David SAMPLE SIZE REQUIREMENT TO SHOW THE EQUIVALENCE OF TWO TREATMENTS IN A PARALELL DESIGN |
| author_facet |
Sotres-Ramos, David |
| author_sort |
Sotres-Ramos, David |
| title |
SAMPLE SIZE REQUIREMENT TO SHOW THE EQUIVALENCE OF TWO TREATMENTS IN A PARALELL DESIGN |
| title_short |
SAMPLE SIZE REQUIREMENT TO SHOW THE EQUIVALENCE OF TWO TREATMENTS IN A PARALELL DESIGN |
| title_full |
SAMPLE SIZE REQUIREMENT TO SHOW THE EQUIVALENCE OF TWO TREATMENTS IN A PARALELL DESIGN |
| title_fullStr |
SAMPLE SIZE REQUIREMENT TO SHOW THE EQUIVALENCE OF TWO TREATMENTS IN A PARALELL DESIGN |
| title_full_unstemmed |
SAMPLE SIZE REQUIREMENT TO SHOW THE EQUIVALENCE OF TWO TREATMENTS IN A PARALELL DESIGN |
| title_sort |
sample size requirement to show the equivalence of two treatments in a paralell design |
| description |
The comparison of two treatments is often formulated on the basis of contrasting hypothesis of the form Ho: m1 = m2 against Ha: m1 ¹ m2 (null and alternative
hipothesis respectively), where m1 and m2 are the population means of each treatment. This formulation of the problem is convenient when the aim is to demonstrate the truth of the alternative
hypothesis, but it is not when the interest is to prove the equivalence of both treatments. For a bioequivalence study, Westlake (1988) developed a procedure to show the equivalence of two
treatments for a crossover design. The aim of this paper is to adapt that procedure for parallel designs, including the sample size formula. The main advantage of this procedure is that it
provides an explicit expression for the sample size for given values of a and b. Its disadvantages are that the real value of the significance level is strictly less than the nominal value of
a, and that it requires that both samples come from normal distributions with equal variances. |
| publisher |
Colegio de Postgraduados |
| publishDate |
1996 |
| url |
https://www.agrociencia-colpos.org/index.php/agrociencia/article/view/1385 |
| work_keys_str_mv |
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