Page's statistic in balanced incomplete block designs

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dc.degree.department Statistics en_US
dc.degree.discipline Statistics en_US
dc.degree.grantor Texas Tech University en_US
dc.degree.level Masters en_US
dc.degree.name M .S . en_US
dc.rights.availability unrestricted en_US
dc.creator Duran , Benjamin S . en_US
dc.date.accessioned 2014 -02 -19T19 :01 :28Z
dc.date.available 2011 -02 -19T00 :59 :52Z en_US
dc.date.available 2014 -02 -19T19 :01 :28Z
dc.date.issued 1995 -08 en_US
dc.identifier.uri http : / /hdl .handle .net /2346 /22456 en_US
dc.description.abstract A block is a collection of experimental units that are as nearly alike as possible relative to the extraneous variable . Each treatment is then randomly assigned to one experimental unit within each block . If the experimental units within blocks are relatively alike and units in different blocks are relatively different , then the randomized complete block design is usually more sensitive to differences in treatment means than the one -way classification design , a design which assumes all experimental units are relatively homogeneous . Often , one may not be able to run all of the treatments in each block . Possible reasons may be due to shortages of experimental units , the physical size of the blocks , or that the cost is too great to use a complete block design . Assuming a complete block design cannot be used , the designer must turn to alternative methods . One popular choice is the randomized incomplete block design , a design which allows for analyzing treatment effects without running every treatment within each block . By assigning treatments in a balanced manner among the experimental units in a block , accurate analysis of treatment effects can be accomplished while reducing the number of treatment runs needed in each block . When performing a normal -theory F test to analyze the treatment effects , the experimenter must assume that the error variables are normally distributed . However , a design could occur in which the normality assumption is invalid , and the designer may wish to use a distribution -free procedure . Nonparametric methods for determinig differences in treatment effects have been proposed for complete randomized block designs by Friedman [3] and for balanced incomplete block designs by Durbin [2] . An analyst may be interested in detecting some specific relationship among the treatment effects . In particular , one may be interested in the simple order alternative , which is useful for testing treatment effects versus a control . For the complete block design , a statistic for the simple order alternative was proposed by Page [5] . We intend to use Page's statistic with incomplete block designs while creating exact distributions for small designs and simulated distributions for larger designs . In the absence of exact or simulated tables , the normal approximation can be used to make a decision with respect to the rejection of the null hypothesis . en_US
dc.language.iso en _US en_US
dc.publisher Texas Tech University en_US
dc.subject Statistics en_US
dc.subject Experimental design en_US
dc.title Page's statistic in balanced incomplete block designs en_US
dc.type Electronic Thesis en_US

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Page's statistic in balanced incomplete block designs. Master's thesis, Texas Tech University. Available electronically from http : / /hdl .handle .net /2346 /22456 .

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