Split-Plot Designs: Follow-Up Experiments, Missing Observations, and Model Adequacy Checking

 
9783838372198: Split-Plot Designs: Follow-Up Experiments, Missing Observations, and Model Adequacy Checking

Split-plot designs are effective in industry due to time and/or cost constraints, restriction on randomization of the treatment combinations of the hard-to-change factors and different sizes of experimental units. Some of the results of fractional factorial split-plot experiments can be ambiguous and a need may arise to conduct follow-up experiments to separate effects of potential interest.The first objective of this research is to extend the foldover technique to break the alias chains of split-plot experiments.Six rules are provided to develop foldovers for minimum aberration resolution III and resolution IV FFSP designs.The second objective is to extend a method due to Draper and Stoneman to estimate missing observations from unreplicated two-level factorial and FFSP designs. The missing observations, which can either be from the same whole-plot, from different WPs, or comprise entire WPs, are estimated by equating to zero a number of specific contrast columns equal to the number of the missing observations.The third objective is to develop numerical and graphical methods to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models.

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Ashraf Almimi
Editorial: LAP Lambert Academic Publishing 2010-06-07 (2010)
ISBN 10: 3838372190 ISBN 13: 9783838372198
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Descripción LAP Lambert Academic Publishing 2010-06-07, 2010. paperback. Estado de conservación: New. Nº de ref. de la librería 9783838372198

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Descripción Estado de conservación: New. Publisher/Verlag: LAP Lambert Academic Publishing | Follow-Up Experiments, Missing Observations, and Model Adequacy Checking | Split-plot designs are effective in industry due to time and/or cost constraints, restriction on randomization of the treatment combinations of the hard-to-change factors and different sizes of experimental units. Some of the results of fractional factorial split-plot experiments can be ambiguous and a need may arise to conduct follow-up experiments to separate effects of potential interest.The first objective of this research is to extend the foldover technique to break the alias chains of split-plot experiments.Six rules are provided to develop foldovers for minimum aberration resolution III and resolution IV FFSP designs.The second objective is to extend a method due to Draper and Stoneman to estimate missing observations from unreplicated two-level factorial and FFSP designs. The missing observations, which can either be from the same whole-plot, from different WPs, or comprise entire WPs, are estimated by equating to zero a number of specific contrast columns equal to the number of the missing observations.The third objective is to develop numerical and graphical methods to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. | Format: Paperback | Language/Sprache: english | 209 gr | 148 pp. Nº de ref. de la librería K9783838372198

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Almimi, Ashraf
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Descripción LAP Lambert Acad. Publ. Jun 2010, 2010. Taschenbuch. Estado de conservación: Neu. This item is printed on demand - Print on Demand Neuware - Split-plot designs are effective in industry due to time and/or cost constraints, restriction on randomization of the treatment combinations of the hard-to-change factors and different sizes of experimental units. Some of the results of fractional factorial split-plot experiments can be ambiguous and a need may arise to conduct follow-up experiments to separate effects of potential interest.The first objective of this research is to extend the foldover technique to break the alias chains of split-plot experiments.Six rules are provided to develop foldovers for minimum aberration resolution III and resolution IV FFSP designs.The second objective is to extend a method due to Draper and Stoneman to estimate missing observations from unreplicated two-level factorial and FFSP designs. The missing observations, which can either be from the same whole-plot, from different WPs, or comprise entire WPs, are estimated by equating to zero a number of specific contrast columns equal to the number of the missing observations.The third objective is to develop numerical and graphical methods to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. 148 pp. Englisch. Nº de ref. de la librería 9783838372198

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Ashraf Almimi
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Descripción LAP Lambert Acad. Publ. Jun 2010, 2010. Taschenbuch. Estado de conservación: Neu. Neuware - Split-plot designs are effective in industry due to time and/or cost constraints, restriction on randomization of the treatment combinations of the hard-to-change factors and different sizes of experimental units. Some of the results of fractional factorial split-plot experiments can be ambiguous and a need may arise to conduct follow-up experiments to separate effects of potential interest.The first objective of this research is to extend the foldover technique to break the alias chains of split-plot experiments.Six rules are provided to develop foldovers for minimum aberration resolution III and resolution IV FFSP designs.The second objective is to extend a method due to Draper and Stoneman to estimate missing observations from unreplicated two-level factorial and FFSP designs. The missing observations, which can either be from the same whole-plot, from different WPs, or comprise entire WPs, are estimated by equating to zero a number of specific contrast columns equal to the number of the missing observations.The third objective is to develop numerical and graphical methods to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. 148 pp. Englisch. Nº de ref. de la librería 9783838372198

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Ashraf Almimi
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Descripción LAP Lambert Acad. Publ. Jun 2010, 2010. Taschenbuch. Estado de conservación: Neu. Neuware - Split-plot designs are effective in industry due to time and/or cost constraints, restriction on randomization of the treatment combinations of the hard-to-change factors and different sizes of experimental units. Some of the results of fractional factorial split-plot experiments can be ambiguous and a need may arise to conduct follow-up experiments to separate effects of potential interest.The first objective of this research is to extend the foldover technique to break the alias chains of split-plot experiments.Six rules are provided to develop foldovers for minimum aberration resolution III and resolution IV FFSP designs.The second objective is to extend a method due to Draper and Stoneman to estimate missing observations from unreplicated two-level factorial and FFSP designs. The missing observations, which can either be from the same whole-plot, from different WPs, or comprise entire WPs, are estimated by equating to zero a number of specific contrast columns equal to the number of the missing observations.The third objective is to develop numerical and graphical methods to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. 148 pp. Englisch. Nº de ref. de la librería 9783838372198

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Ashraf Almimi
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Descripción LAP Lambert Academic Publishing, 2010. PAP. Estado de conservación: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería IQ-9783838372198

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Ashraf Almimi
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Descripción LAP Lambert Academic Publishing, Germany, 2010. Paperback. Estado de conservación: New. Language: English . Brand New Book ***** Print on Demand *****.Split-plot designs are effective in industry due to time and/or cost constraints, restriction on randomization of the treatment combinations of the hard-to-change factors and different sizes of experimental units. Some of the results of fractional factorial split-plot experiments can be ambiguous and a need may arise to conduct follow-up experiments to separate effects of potential interest.The first objective of this research is to extend the foldover technique to break the alias chains of split-plot experiments.Six rules are provided to develop foldovers for minimum aberration resolution III and resolution IV FFSP designs.The second objective is to extend a method due to Draper and Stoneman to estimate missing observations from unreplicated two-level factorial and FFSP designs. The missing observations, which can either be from the same whole-plot, from different WPs, or comprise entire WPs, are estimated by equating to zero a number of specific contrast columns equal to the number of the missing observations.The third objective is to develop numerical and graphical methods to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. Nº de ref. de la librería AAV9783838372198

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