A procedure for allocating heterogenous units to treatment groups

In allocating experimental subjects that are not homogeneous (eg. animals, socio-economic units such as households, etc.) to treatment groups, certain attributes which are likely to affect the results if not accounted for, are usually used as classification variables prior to allocation. This can ea...

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Detalles Bibliográficos
Autores principales: Nokoe, S., Zewdie, S.
Formato: Journal Article
Lenguaje:Inglés
Publicado: 2000
Materias:
Acceso en línea:https://hdl.handle.net/10568/99894
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author Nokoe, S.
Zewdie, S.
author_browse Nokoe, S.
Zewdie, S.
author_facet Nokoe, S.
Zewdie, S.
author_sort Nokoe, S.
collection Repository of Agricultural Research Outputs (CGSpace)
description In allocating experimental subjects that are not homogeneous (eg. animals, socio-economic units such as households, etc.) to treatment groups, certain attributes which are likely to affect the results if not accounted for, are usually used as classification variables prior to allocation. This can easily be done for one or two variables by dividing the observed range(s) of the key classification variable(s) into sub-groups and ensuring, as far as possible, that treatments appear in all groups (as in balanced designs) or some treatments or subjects are not disadvantaged as in unbalanced or in unequal replication scenarios. Several conflicting allocation results are likely if done independently for more than 2 important variables. This paper suggests the use of a multivariate procedure to achieve an effective allocation of treatments. The method is illustrated with data on 24 animals from 2 breeds of crossbred dairy cows for allocation to 6 treatment groups (2 diet types and 3 levels of draught work). An extension to the use of the method is provided for selection of socio-economic units.
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spelling CGSpace998942023-06-12T14:30:50Z A procedure for allocating heterogenous units to treatment groups Nokoe, S. Zewdie, S. socioeconomic development experimental design In allocating experimental subjects that are not homogeneous (eg. animals, socio-economic units such as households, etc.) to treatment groups, certain attributes which are likely to affect the results if not accounted for, are usually used as classification variables prior to allocation. This can easily be done for one or two variables by dividing the observed range(s) of the key classification variable(s) into sub-groups and ensuring, as far as possible, that treatments appear in all groups (as in balanced designs) or some treatments or subjects are not disadvantaged as in unbalanced or in unequal replication scenarios. Several conflicting allocation results are likely if done independently for more than 2 important variables. This paper suggests the use of a multivariate procedure to achieve an effective allocation of treatments. The method is illustrated with data on 24 animals from 2 breeds of crossbred dairy cows for allocation to 6 treatment groups (2 diet types and 3 levels of draught work). An extension to the use of the method is provided for selection of socio-economic units. 2000 2019-03-03T05:53:52Z 2019-03-03T05:53:52Z Journal Article https://hdl.handle.net/10568/99894 en Limited Access Nokoe, S. & Zewdie, S. (2000). A procedure for allocating heterogeneous units to treatment groups. Discovery and Innovation, 12(3/4), 179-198.
spellingShingle socioeconomic development
experimental design
Nokoe, S.
Zewdie, S.
A procedure for allocating heterogenous units to treatment groups
title A procedure for allocating heterogenous units to treatment groups
title_full A procedure for allocating heterogenous units to treatment groups
title_fullStr A procedure for allocating heterogenous units to treatment groups
title_full_unstemmed A procedure for allocating heterogenous units to treatment groups
title_short A procedure for allocating heterogenous units to treatment groups
title_sort procedure for allocating heterogenous units to treatment groups
topic socioeconomic development
experimental design
url https://hdl.handle.net/10568/99894
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