[Limdep Nlogit List] Test if blocks in the design created a bias.

Brett Smith brett.smith at uwa.edu.au
Mon Jun 12 13:45:04 AEST 2017


Hi Damien,

The alternate specific constants relate to the alternatives 1,2,3 and as these are unlabelled alternatives the ASC should not differ from zero (no matter which block the respondent answered). Perhaps you may look at the taste parameters. One possibility is to use the panel specification and to set the parameters to random (I am not sure how many responses you have so you may want to be cautious). Interact the R.P. with choice blocks 2 and 3. If the location of the mean parameter estimates differ from zero then that is an indicator that there is a design effect in your data.

All the best,

Brett

-----Original Message-----
From: limdep-bounces at limdep.itls.usyd.edu.au [mailto:limdep-bounces at limdep.itls.usyd.edu.au] On Behalf Of Damien Jourdain
Sent: Monday, 12 June 2017 11:18 AM
To: limdep at limdep.itls.usyd.edu.au
Subject: [Limdep Nlogit List] Test if blocks in the design created a bias.

Dear all, 

 

We have conducted a discrete choice experiment using a D-efficient design with 18 scenarios. As we were concerned that 18 scenarios would create too much burden for respondents, we decided to create 3 blocks of 6 scenarios.

 

The population of the 3 blocks were chosen to be as similar as possible, but since not all people received the same scenarios, we would like to test whether we haven't created a bias. 

 

It is an unlabeled experiment with one status quo option. We have introduced a dummy variable ASC (1 when SQ, 0 other alternative), and two dummy variables for block2 and block3. 

 

We want to test that blocks did not introduce some bias, so we are testing the interactions of blocks with the ASC variable (as we would test the influence of socio-economic variables)

 

? MNL Model

NLOGIT; 

    ; Choices = 1,2,3

    ; Lhs = choice

    ; Rhs = asc, asc*block2, asc*block3 , prim, wbird, iweed, fecos 

$

 

If the coefficient associated to asc*block1 and asc*block2 are not significantly different from zero, can we say that the block did not
introduce biases?   Or should we use another test?

 

Would this formulation still work if we were using effect coding for both ASC and block2 and block3? 

 

Best,

 

Damien

 

 

Dr. Damien Jourdain

Agricultural and Natural Resources Economist

Visiting Assistant Professor

Asian Institute of Technology / CIRAD G-EAU

Natural Resource Management / Water Engineering and Management

 

mail: djourdain at ait.asia

 

web GEAU : www.g-eau.net <http://www.g-eau.net/>  

web NRM :  <http://www.nrm.ait.asia/> www.nrm.ait.asia

 

 

 

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