Talk:ERF for Frambozadrine in rats: Difference between revisions

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|Outcome= Under discussion (to be changed when a conclusion is found)
|Outcome= Under discussion (to be changed when a conclusion is found)
|Argumentation =
|Argumentation =
{{defend|#1: |Method A is the best.|--[[User:Jouni|Jouni]] 14:26, 24 October 2007 (EEST)}}<br>
{{defend_invalid|#1: |Method A is the best.|--[[User:Jouni|Jouni]] 14:26, 24 October 2007 (EEST)}}<br>
:{{attack|#(8): |I assume the confidence bands eg in sheet nr 6 mean that you are 90% confident that the probability P(d) of response at dose d lies between the bounds. If you consider the P(d) mixture of binomials at dose d, with the number of animals from the original data, then shouldnt the actual number of responses at dose d lie within the corresponding bounds 90% of the time? I dont think that will be the case. In otherwords, we could look at these confidence bands as a statistical hypothesis, and it looks to me like it would be rejected on this data. |--[[User:Roger|Roger]] 17:02, 24 October 2007 (EEST)}}
{{attack|#2: |Method B is the best.|--[[User:Jouni|Jouni]] 14:26, 24 October 2007 (EEST)}}
{{attack|#2: |Method B is the best.|--[[User:Jouni|Jouni]] 14:26, 24 October 2007 (EEST)}}
:{{defend|#5: |B recovers the observed uncertainty the best when inversion works out.|by Roger Cooke, added by --[[User:Jouni|Jouni]] 14:26, 24 October 2007 (EEST)}}
:{{defend|#5: |B recovers the observed uncertainty the best when inversion works out.|by Roger Cooke, added by --[[User:Jouni|Jouni]] 14:26, 24 October 2007 (EEST)}}

Revision as of 14:02, 24 October 2007

Which method is the best for dose-response estimation?

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←--#1:: . Method A is the best. --Jouni 14:26, 24 October 2007 (EEST) (type: truth; paradigms: science: defence)

⇤--#(8):: . I assume the confidence bands eg in sheet nr 6 mean that you are 90% confident that the probability P(d) of response at dose d lies between the bounds. If you consider the P(d) mixture of binomials at dose d, with the number of animals from the original data, then shouldnt the actual number of responses at dose d lie within the corresponding bounds 90% of the time? I dont think that will be the case. In otherwords, we could look at these confidence bands as a statistical hypothesis, and it looks to me like it would be rejected on this data. --Roger 17:02, 24 October 2007 (EEST) (type: truth; paradigms: science: attack)

⇤--#2:: . Method B is the best. --Jouni 14:26, 24 October 2007 (EEST) (type: truth; paradigms: science: attack)

←--#5:: . B recovers the observed uncertainty the best when inversion works out. by Roger Cooke, added by --Jouni 14:26, 24 October 2007 (EEST) (type: truth; paradigms: science: defence)
⇤--#6:: . Probabilistic inversion is a demanding method and does not converge more often than others. by Roger Cooke, added by --Jouni 14:26, 24 October 2007 (EEST) (type: truth; paradigms: science: attack)
⇤--#(7):: . Jouni didn't say it quite right, PI always converges, but it converges to a SOLUTION only if the problem is feasible. When the PI problem is not feasible, it converges to a 'minimally painful' answer. In this case the PI was feasible for the threshold model. --Roger 16:25, 24 October 2007 (EEST) (type: truth; paradigms: science: attack)

⇤--#3:: . Method C is the best. --Jouni 14:26, 24 October 2007 (EEST) (type: truth; paradigms: science: attack)

⇤--#4:: . Method D is the best. --Jouni 14:26, 24 October 2007 (EEST) (type: truth; paradigms: science: attack)
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