000			03056nab a22003977a 4500
001			G95078
003			MX-TxCIM
005			20240919020946.0
008			210805t2011 xxk|||p|op||| 00| 0 eng d
022			_a1475-2735 (Online)
022	0		_a0960-2585
024	8		_ahttps://doi.org/10.1017/S0960258511000055
040			_aMX-TxCIM
041			_aeng
090			_aCIS-6348
100	1		_aMontesinos-Lopez, O.A. _8I1706800 _92700 _gGenetic Resources Program
245	1	0	_aOptimal sample size for estimating the proportion of transgenic plants using the Dorfman model with a random confidence interval
260			_aCambridge (United Kingdom) : _bCambridge University Press, _c2011.
500			_aPeer review
500			_aPeer-review: Yes - Open Access: Yes|http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0960-2585
520			_aGroup testing is a procedure in which groups that contain several units (plants) are analysed without having to inspect individual plants, with the purpose of estimating the prevalence of genetically modified plants (adventitious presence of unwanted transgenic plants, AP) in a population at a low cost, without losing precision. When pool (group) testing is used to estimate the proportion of AP (p), there are several procedures that can be used for computing the confidence interval (CI); however, they usually do not ensure precision in the estimation of p. This research proposes a formula for determining the required number of pools (g), given a pool size (k), for estimating the proportion of AP plants using the Dorfman model. The proposed formula ensures precision in the estimated proportion of AP because it guarantees that the width (W) of the CI will be equal to, or narrower than, the desired width (v), with a probability of g. This probability accounts for the stochastic nature of the sample variance of p. We give examples to show how to use the proposed sample size formula. Simulated data were created and tables are presented showing the different scenarios that a researcher may encounter. The Monte Carlo method was used to study the coverage and the level of assurance achieved by the proposed sample sizes. An R program that reproduces the results in the tables and makes it easy for the researcher to create other scenarios is given in the Appendix.
536			_aGenetic Resources Program
546			_aText in English
591			_aCambridge University Press
594			_aCCJL01
650		7	_aTransgenic plants _2AGROVOC _94329
650		7	_aStatistical methods _2AGROVOC _92624
650		7	_aSampling _2AGROVOC _96084
700	1		_92702 _aMontesinos-Lopez, A.
700	1		_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959
700	1		_92704 _aEskridge, K.
700	1		_921897 _aSáenz, R.A.
773	0		_tSeed Science Research _gv. 21, no. 3, p. 235-245 _dCambridge (United Kingdom) : Cambridge University Press, 2011. _wG96711 _x0960-2585
856	4		_yAccess only for CIMMYT Staff _uhttps://hdl.handle.net/20.500.12665/264
942			_cJA _2ddc _n0
999			_c28398 _d28398