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Scaled Logitic Model
Hi- need to fit the following logistic model to data, where Y=binary (1=diseased, 0=no-disease) and X is continuous. The model is similar to a logistic but with an added parameter, lambda. Any advice on how to proceed in JMP will be appreciated.
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Re: Scaled Logitic Model
Hi @vincem : That is the Logistic 3p model in the Nonlinear platform Model Library, where lambda (your model) = theta1, alpha ( your model) = ln(theta2), beta (your model) = theta3.
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Re: Scaled Logitic Model
thank you very much. however my response is biinary (diseased =1, or not diseased=0) im unsure whether the non-linear platfrom can handle a binary response. appreciate your help. thanks again.
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Re: Scaled Logitic Model
Hi @vincem It can be done via the method described by @peng_liu here. The log-likelihood will be different though. See here.
And see section 12.2.1 here (you will need to adapt it slightly to include lambda).
https://www.stat.cmu.edu/~cshalizi/uADA/12/lectures/ch12.pdf
for the log-likelihood function (use the negative log-likelihood as @peng_liu explains)
Questions, come back.
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Re: Scaled Logitic Model
Thanks again..I have fitted the nonlinear model and fitted the below, where prop=n/N in below table. Parameter estimates noted below. i think its worked as its should..
Data is from the publication
https://pubmed.ncbi.nlm.nih.gov/21983214/
titres | vaccine | n | N | prop |
5 | Non-Flu | 6 | 119 | 0.05042 |
20 | Non-Flu | 0 | 2 | 0 |
40 | Non-Flu | 0 | 1 | 0 |
80 | Non-Flu | 0 | 4 | 0 |
160 | Non-Flu | 0 | 7 | 0 |
320 | Non-Flu | 0 | 13 | 0 |
453 | Non-Flu | 0 | 1 | 0 |
640 | Non-Flu | 0 | 4 | 0 |
2560 | Non-Flu | 0 | 1 | 0 |
3620 | Non-Flu | 0 | 1 | 0 |
5 | TIV Control | 2 | 25 | 0.08 |
10 | TIV Control | 2 | 36 | 0.055556 |
20 | TIV Control | 4 | 47 | 0.085106 |
28 | TIV Control | 0 | 1 | 0 |
40 | TIV Control | 2 | 42 | 0.047619 |
57 | TIV Control | 0 | 1 | 0 |
80 | TIV Control | 4 | 28 | 0.142857 |
113 | TIV Control | 0 | 1 | 0 |
160 | TIV Control | 0 | 32 | 0 |
226 | TIV Control | 0 | 1 | 0 |
320 | TIV Control | 0 | 17 | 0 |
640 | TIV Control | 0 | 16 | 0 |
905 | TIV Control | 0 | 2 | 0 |
1280 | TIV Control | 0 | 35 | 0 |
1810 | TIV Control | 0 | 4 | 0 |
2560 | TIV Control | 0 | 19 | 0 |
3620 | TIV Control | 0 | 2 | 0 |
5120 | TIV Control | 0 | 4 | 0 |
5 | TIV adj | 0 | 4 | 0 |
40 | TIV adj | 0 | 1 | 0 |
80 | TIV adj | 0 | 1 | 0 |
160 | TIV adj | 0 | 21 | 0 |
226 | TIV adj | 0 | 2 | 0 |
320 | TIV adj | 0 | 63 | 0 |
453 | TIV adj | 0 | 7 | 0 |
640 | TIV adj | 1 | 76 | 0.013158 |
905 | TIV adj | 0 | 4 | 0 |
1280 | TIV adj | 1 | 63 | 0.015873 |
1810 | TIV adj | 0 | 4 | 0 |
2560 | TIV adj | 0 | 46 | 0 |
3620 | TIV adj | 0 | 9 | 0 |
5120 | TIV adj | 0 | 10 | 0 |