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From |
Jacky Haskell <kemp.jacky@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Effects coding and nested logit in Stata |

Date |
Fri, 14 Aug 2009 10:27:41 -0400 |

Dear all, I am analyzing data from a choice experiment and am trying to figure out what is the correct way of effects coding to run nested logit. In each choice question, there are three alternatives: Contract A, Contract B, or Not Buy. Each alternative is characterized by four attributes. One of the attributes ("survival") has four possible levels in Contracts A and B, and is always at a status quo level in the Not Buy alternative; this status quo level is not included in the four attribute levels in the contracts. Initially, I used effects codes as follows: three "survival" variables (survival1, survival2, survival3) representing each of the first three attribute levels, using the fourth level as a base (a value of -1 for all three variables), and entering all zeros for the status quo. So the values for [survival1, survival2, survival3] with effect codes looks like this: level 1: 1, 0, 0 level 2: 0, 1, 0 level 3: 0, 0, 1 level 4: -1, -1, -1 not buy: 0, 0, 0 I then estimated a nested logit model in Stata 10 using the following commands: nlogitgen type=alternative(yes: 1 | 2, no: 3) label list lb_type nlogittree alternative type, choice(choice) nlogit choice survival1 survival2 survival3 acres access1 access2 access3 cost || type: || alternative:, noconstant case(idq) The model was estimated, but Stata gave the following message: note: variable survival1 has 296 cases that are not alternative-specific: there is no within-case variability note: variable survival2 has 274 cases that are not alternative-specific: there is no within-case variability note: variable survival3 has 277 cases that are not alternative-specific: there is no within-case variability I believe that the lack of within-case variability occurs whenever a survival variable has all zeros for all three alternatives; for example, if Contract A has survival level 2, Contract B has survival level 3, and Not Buy is always the status quo level, then the variable survival1 will have a value of zero for all three alternatives. To avoid this problem, I changed the effects codes to the following: the same three "survival" variables, but this time using the status quo level as a base (a value of -1 for all three variables), and entering all zeros for the fourth attribute level. Now the values for the variables [survival1, survival2, survival3] with effect codes looks like this: level 1: 1, 0, 0 level 2: 0, 1, 0 level 3: 0, 0, 1 level 4: 0, 0, 0 not buy: -1, -1, -1 When I run the model with this set of effect codes, there is no longer an error message. The "cost" variable's parameter estimate is unchanged, but the survival variables' estimates are different, causing a significant difference in the resulting willingness-to-pay estimates obtained from the two models. My question is, which model is correct? Has anyone come across a similar problem? Thank you, Jacky Kemp * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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