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Table 2 Simulation results: estimations of bias and mean squared error for the exponential model

From: Estimating time-to-onset of adverse drug reactions from spontaneous reporting databases

     Naive estimator   TBE  
λ p n BIAS( λ ̂ ) MSE( λ ̂ ) BIAS( λ ̂ ) MSE( λ ̂ ) NPM
0.05 0.25 100 0.498 0.250 0.030 0.005 224
   500 0.498 0.248 0.007 0.001 79
0.05 0.50 100 0.195 0.038 0.008 0.001 85
   500 0.193 0.037 <0.001 <0.001 1
0.05 0.80 100 0.073 0.005 <0.001 <0.001 2
   500 0.072 0.005 <0.001 <0.001 0
1 0.25 100 10.06 102 0.462 2.17 72
   500 9.95 99 0.046 0.48 10
1 0.50 100 3.91 15.4 0.126 0.49 29
   500 3.86 14.9 -0.022 0.12 0
1 0.80 100 1.45 2.16 0.004 0.11 0
   500 1.45 2.11 0.004 0.02 0
  1. The mean squared error formula is MSE( λ ̂ )=Var( λ ̂ )+ ( BIAS ( λ ̂ ) ) 2 . Calculations were made on the replications where there was no problem of maximization. In the last column appear the number of problems of maximization for the truncation-based approach. There was no problem of maximization for the naive approach. Abbreviations: TBE truncation-based estimator, MSE mean squared error, NPM number of maximization problems.
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