000			03449nab a22004097a 4500
001			G63978
003			MX-TxCIM
005			20240919020944.0
008			210726s1997 xxu|||p|op||| 00| 0 eng d
022			_a1435-0653 (Online)
022			_a0011-183X
024	8		_ahttps://doi.org/10.2135/cropsci1997.0011183X003700020017x
040			_aMX-TxCIM
041			_aeng
072		0	_aF01
072		0	_aU10
090			_aCIS-4380
100	1		_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959
245	1	0	_aSites regression and shifted multiplicative model clustering of cultivar trial sites under heterogeneity of error variances
260			_aMadison (USA) : _bCSSA : _bWiley, _c1997.
340			_aComputer File Printed
500			_aPeer review
500			_aPeer-review: Yes - Open Access: Yes|http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0011-183X
520			_aPrevious papers have developed the shifted multiplicative model with one multiplicative term (SHMM1) as a model for clustering yield trial sites or cultivars into groups in which cultivar rank changes are statistically negligible. Properties of SHMM1 are proportionality of predicted cultivar differences within sites, and of site differences within cultivars. The latter constraint is relaxed if the sites regression model with one multiplicative term (SREG1) is used instead of SHMM1. Dendrograms for the two methods are identical, but SHMM and SREG analyses of clusters suggested by the dendrogram may lead to different conclusions concerning acceptability of a particular cluster. This study compared SREG clustering to SHMM clustering in two international maize (Zea mays) cultivar trials, when the data to which models were fitted were original unscaled cell means, and, as a way to cope with site to site heterogeneity of error variance, cell means scaled by dividing by the standard error of a cultivar mean within the particular site. Results of both trials confirmed the expectation that SREG clustering would occasionally allow clusters to merge which would not be statistically acceptable under SHMM analysis. This occurred at a cost of a modest increase in percentage and magnitude of significant crossover interactions within the clusters. Both trials exhibited significant site to site heterogeneity of error variances. Scaling of data resulted in more effective removal of significant rank-change interactions from within clusters, provided that the test criterion was based on the assumption of heterogeneous variance. Besides occasionally allowing larger clusters, advantages for SREG clustering of sites are (i) all solutions (including constrained non-crossover solutions) exist in closed form and (ii) the analysis of scaled data is equivalent to a weighted least squares analysis, neither of which holds for SHMM
536			_aGenetic Resources Program
546			_aText in English
591			_a9705|Crop Science Society of America (CSSA)|EE|R97ANALY|Maria|Fdo|1
594			_aCCJL01
650		7	_aCrops _91069 _2AGROVOC
650		7	_aStatistical methods _92624 _2AGROVOC
650		7	_aVariety trials _92474 _2AGROVOC
653	0		_aCIMMYT
700	1		_aCornelius, P.L. _99555
773	0		_tCrop Science _n630748 _gv. 37, no. 2, p. 406-415 _dMadison (USA) : CSSA : Wiley, 1997. _wG444244 _x1435-0653
856	4		_yAccess only for CIMMYT Staff _uhttps://hdl.handle.net/20.500.12665/328
942			_cJA _2ddc _n0
999			_c18457 _d18457