Log in
Register|
martin ★★ Austria, 2018-07-23 22:17 (2897 d 09:39 ago) Posting: # 19086 Views: 5,193 |
|
|
Dear colleagues, I would be happy to get the forum members thoughts regarding graphical display of the outcome of a dose-proportionality assessment based on the power-law model In case that the power law model used to assess dose proportionality consists only of fixed factors intercept and slope I would think a figure like Figure 1 and 3 in the Smith et al paper (Smith et al. , 2000. Confidence interval criteria for assessment of dose proportionality. Pharm Res. 17:1278-1283) is good way to go. However, frequently the corresponding model includes period and sequence effect as additional fixed effects (e.g. Williams design) and I am looking for some thoughts how to adequately visualize the corresponding results (other than showing the observed data and corresponding predictions grouped by sequence and period in a lattice plot or residual plots). Best regards Martin |
|
d_labes ★★★ Berlin, Germany, 2018-07-26 16:49 (2894 d 15:07 ago) @ martin Posting: # 19105 Views: 4,167 |
|
|
Dear Martin, ❝ In case that the power law model used to assess dose proportionality consists only of fixed factors intercept and slope I would think a figure like Figure 1 and 3 in the Smith et al paper (Smith et al. , 2000. Confidence interval criteria for assessment of dose proportionality. Pharm Res. 17:1278-1283) is good way to go. I think so. ❝ However, frequently the corresponding model includes period and sequence effect as additional fixed effects (e.g. Williams design) and I am looking for some thoughts how to adequately visualize the corresponding results (other than showing the observed data and corresponding predictions grouped by sequence and period in a lattice plot or residual plots). For sake of simplicity I would go with the same plots as in the first case. Only if period effects and/or sequence effects have a greater magnitude than the power law you will have a scatter in the data which seems not fit. I would expect such an behavior in only very rare cases, if any. If you have such a case, 'correct' your data for the period and/or sequence effects and plot then. Hope you are well. — Regards, Detlew |
Ing. Helmut Schütz