Bernard The bootstrap method is intended to give you a reliable measurement of the uncertainty of the estimates. The interest is then to obtain, for example, the median and the 95% confidence interval of estimates via the 2.5th and 97.5th quantiles of each parameter. So I think it is not really necessary to look at the bootstrap statistics on the SEs produced by the Nonmem output (in my experience and probably that of other users, SEs produced by Nonmem may vary with initial values, or the $COV step can be achieved or not also depending on initial estimates). I personally use to remove the $COV when I do a bootstrap via WfN
Hope that it heps Saik ----- Original Message ----- From: Bernard ROYER To: [email protected] Sent: Wednesday, April 23, 2008 11:01 AM Subject: [NMusers] NMVI and SEs assessment Dear NMusers, I have questions about bootstraping and NONMEM VI assement of SEs. I have developed a 2-compartment PK model using NMVI that converged with estimations of THETAs and OMEGAs. The predictive check simulations indicated that the model satisfactorily described the data with parameters estimated by NMVI. Then I started the assement of SEs by boostrating the data using WFN (1000 resamplings). I found similar results for THETAs, OMEGAs and SIGMAs (mixt error used). About the results of SEs, I also found similar results for the SEs of THETA1 (Volume), THETA2 (Clearance), OMEGAs and SIGMA1 (proportional part), but not for the SEs of THETA3 nor THETA4 (K12 and K21) and the SIGMA2 (residual error). I think that the actual values are more close of those obtained with bootstrap than those obtained with NMVI. The results of the obtained SEs are described in the table below. I also performed a run with the same Input and data set with NMV and the results are also described in the table (NMV gives same results for thetas, omegas, sigmas and OFV). SE of: NMVI values Bootstrap values NMV values THETA1 0.148 0.154 0.154 THETA2 0.00218 0.00242 0.0227 THETA3 0.00063 0.0013 0.0013 THETA4 0.00036 0.0022 0.0019 OMEGA1 0.0094 0.0095 0.0094 OMEGA2 0.0050 0.0054 0.0051 SIGMA1 0.0063 0.0064 0.0064 SIGMA2 0.675 0.946 0.832 My questions are: - Why NMVI gives evaluations of SE less reliable than NMV ? and why only for THETA3, THETA4 and SIGMA 1 - for covariates determination wiht NMVI, do I need to perform bootstrap for each covariate or taking into account the decrease of omega is sufficient ? - The value of residual error obtained with NMVI is 1.69 (SE = 0.675). The value obtained with boostrap is 1.58 (SE = 0.95), thus zero is included in IC95. How interpreting residual error including zero in IC95 with boostrap but not with NMVI. Removing SIGMA2 leads to failure of the run. Should I fix this value or leaving it with its SE ? Bernard Royer Pharmacology Dpt University Hospital Besancon, France
