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The SoV probit [electronic resource] : a probit model with structured covariance for similarity effects and source of volume calculations / Jeff Brazell.

By: Material type: FilmPublisher number: 2678 | Henry Stewart TalksSeries: Henry Stewart talks. Marketing & management collection. Bayesian analysis in marketingPublication details: London : Henry Stewart Talks, 2010.Description: 1 online resource (1 streaming video file (41 min.) : color, sound)Subject(s): Online resources:
Contents:
Contents: Source of volume and cannibalization -- Product and line optimization questions -- Quick definitions -- Red bus / blue bus example -- What is IID? and IIA? -- We know IIA/IID gets source-of-volume wrong -- When should we care about substitution patterns? -- Source of volume calculations -- Cannibalization = Preference -- How do you handle IIA in your choice models? -- Simulating preference shares: state-of-the-art -- What does proportional substitution look like? -- Industry survey: how do current methods do? -- The SoV Probit -- Why should I care about correlated errors? -- Why aren't we all using Probit models? -- A structured covariance Probit -- Distance metrics -- Choice experiment -- Model fit statistics -- Parameter estimates -- WTP comparison -- Representative correlation matrix -- Does it work?
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Animated audio-visual presentation with synchronized narration.

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Contents: Source of volume and cannibalization -- Product and line optimization questions -- Quick definitions -- Red bus / blue bus example -- What is IID? and IIA? -- We know IIA/IID gets source-of-volume wrong -- When should we care about substitution patterns? -- Source of volume calculations -- Cannibalization = Preference -- How do you handle IIA in your choice models? -- Simulating preference shares: state-of-the-art -- What does proportional substitution look like? -- Industry survey: how do current methods do? -- The SoV Probit -- Why should I care about correlated errors? -- Why aren't we all using Probit models? -- A structured covariance Probit -- Distance metrics -- Choice experiment -- Model fit statistics -- Parameter estimates -- WTP comparison -- Representative correlation matrix -- Does it work?

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