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Optimal designs for estimating a choice hierarchy by a general nested multinomial logit model
Wilfrido Jacobo Paredes-García, Eduardo Castaño‐Tostado

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The article discusses how to better understand decision-making in choice experiments using a Nested Multinomial Logit Model. The researchers developed a likelihood function for a two-stage NMNL model and found optimal designs for scenarios with multiple alternatives. These designs can provide more reliable answers with less complexity.