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The approach taken to deal with uncertainty in the estimates is consequently statistical and not based on sensitivity analyses.
For small lags, the variance of the estimates is small, but the estimation is highly biased.
The maximum number K should be much smaller than the sample size to ensure the parameters are estimable and the variation of the estimates is not overly large.
However, our estimations reveal that the difference in the estimates is much larger for immigrants than for natives.
We observe that the scatter in the estimates is reducing while the optimization procedure progresses, but our estimators are biased.
The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated.
As for the smaller sample size, the variability of the estimates is higher; however, both current cumulative incidence and current leukaemia-free survival estimators have comparable performance to the Markov model estimator.
The real problem with the estimates is that the outcome may be worse than expected.
However, uncertainty in the estimates is high.
The variance of the estimates is shown in Figure 10b.
The effect of duration of data on the estimates is also investigated.
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