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 |