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From |
"Ronnie Babigumira" <ronnie.babigumira@umb.no> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: RE: Multiple responses on plot level data |

Date |
Fri, 22 Apr 2005 16:37:17 +0200 |

Hi all Nick, Rafael, and Menale, many thanks for your input. Let me try to take stock of what I know so far, the problem was that I have plot level data (with some household specific variables). The response variable(s) are choice of conservation measure (three possible choices fert, man, fanyaju). hhd_id plnum fert man fanyaju (and a number of predictor variables) 1001 1 0 1 0 1001 2 0 1 1 1001 3 1 0 1 1002 1 0 0 0 1002 2 1 1 1 1003 1 1 0 0 Here is what has been suggested A. Simplest solution Estimate a simple probit/logit for each of the three measures (fert, man, and fanyaju). This would allow us to examine the effect of the predictor variables on the odds of choosing a particular measure versus all other measures including none of them. We are not able to say anything about the odds of A vs B but rather A vs all other choices. B. Even better Use a multinomial logit. This is more interesting because in my understanding, it allows us to examine the effect of the predictor variables on the odds of choosing A vs B, or A vs C (and all other combinations). I much prefer this however, for my data, this presents an additional challenge. If each plot could have only one of the 3 then we would be home and dry, however as we see for plot 2 of 1001, a plot could have 2, or even 3 for 1002, plot 2 and herein lies my challenge Menale has proposed that we add more observations. He proposes that we create a new variable, choice which takes on the values 1,2,3 for fert, man, and fanyaju rspv. So the data according to his proposal would then look like hhd_id plnum choice 1001 1 2 1001 2 2 1001 2 3 1001 3 1 1001 3 3 1002 1 0 1002 2 1 1002 2 2 1002 2 3 1003 1 1 This would appear OK to me, however, my concern is that now you have clustering at both the household and plot level. Would this be a problem? Nick on the other hand proposes that in addition to the 4 clean classes (0, 1, 2, 3), we add 5 6 and 7 which reflect diffrent combinatons of the three. Some thing like this fert 1 man 2 fanyaju 3 fert/man 4 man/fanyaju 5 fert/fanyaju 6 fert/man/fanyaju 7 none 0 The data according to Nicks proposal would look something like this hhd_id plnum Choice 1001 1 2 1001 2 5 1001 3 6 1002 1 0 1002 2 7 1003 1 1 I have some concerns with this, particulary that choices 4/7 are combinations of the 1/3. Isnt this a problem (forgive my ignorance, but doesnt this point in the direction of the IIA problem). Finally Rafael recommends a diffrent approach. Im still working through his posting and will get back to him in a lil. So, here I am, more ideas, a little more confusion, certainly non the wiser. I would appreciate comments. Ronnie >>> menale kassie <dawitkassie@yahoo.com> 04/22/05 1:01 am >>> What is the problem if one repeats those plots that have more than one conservation measure within the household? Assume one household has three plots. One of the plots has two conservation measures and assumes others have one conservation measure. Then when we repeat the plot with two conservation measures the household will have four plots observation. Look at the following example. Hhno plotno fert manure fanya juu 1 1 1 1 0 1 2 0 1 0 1 3 0 0 1 then repeating the first plot you can construct one dependent variable as follow hhno plot Y 1 1 1 1 1 2 1 2 2 1 3 3 where 1= fert, 2= manure, 3= fanya juu, and Y dependent variables Hope this is right. Menale K Ronnie Babigumira <ronnie.babigumira@umb.no> wrote:Thanks Nick, sorry for the lack of clarity, measure choice is my response (dependent is the term Im more farmiliar with) variable (s). I do have a set of predictor (independent) variables which I did not include in my email. Yes I did consider logit models for individual responses. I also considered constructing a dependent variable indicating whether or not any one of the choices was made. However, I have been thinking about the mlogit. So you say 8 possible choices, would that mean 1, 2, 3 for fert, man, fanyaju rspv and then 5/8 for the diffrent combinations of each. If so, doesnt isnt this a problem because the classes are not exactly independent in the sense that (say 5 if choices 2 and 3 were made on the plot) Ronnie Ronnie Babigumira Dept. of Economics and Resource Management Norwegian University of Life Sciences (UMB) PO Box 5003, N-1432 *s, Norway >>> n.j.cox@durham.ac.uk 04/21/05 4:30 PM >>> I am not clear whether you regard measure choice as a predictor or a response. And in any case I can imagine situations in which both views are reasonable. Soil erosion loss could depend on conservation measures, which choice of conservation measures might depend on many things. If it were the latter, I think it is up to you how you define a composite response. Nor is it clear to me that you need do that. If this were my problem I would look at (a) logit models for the individual responses and (b) a multinomial logit for the 8 possible choices of fert[iliser?] man[ure?] and fanyaju[???]. If conservation measures are predictors, you would need to look not just at dummies but also at interactions. Nick n.j.cox@durham.ac.uk Ronnie Babigumira > Something has been slowly eating away at me and at this point I have > decided to seek help from the list. I have plot level data on use of > soil conservation measures and would like to construct a "single" > dependent variable for each household for use in a multinomial logit. > The data look something like this > > hhd_id plnum fert man fanyaju > 1001 1 0 1 0 > 1001 2 0 1 1 > 1001 3 1 0 1 > 1002 1 0 0 0 > 1002 2 1 1 1 > 1003 1 1 0 0 > > Where > hhd_id: Household id > plnum: Plot number (a household may have more than one plot) > And fert, man and fanyaju are 3 possible soil conservation measures a > household may undertake (it is possible that more than one measure can > be applied to a plot) > > My question is how do I go about with constructing a single dependent > variable for use in a multinomial logit in this case (and > would this be > correct). I have considered the simplest case where I > construct a simple > dummy for each plot indicating whether or not a household > used at least > one of the measures however, I feel that it would be more > interesting if > I could say something on the determinants for the use of the different > measures * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ __________________________________________________ Do You Yahoo!? Tired of spam? Yahoo! Mail has the best spam protection around http://mail.yahoo.com * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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