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Table 1 Piecewise exponential regression excess mortality models with and without correcting for overdispesion, n = 376,791 women diagnosed with breast cancer in England between 1997 and the end of 2005

From: Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research

  PEREM A PEREM B (scaled SE) PEREM C (Robust SE) PEREM D (NBR)
Age at diagnosis EMRR SE EMRR SE RLE (%) EMRR SE RLE (%) EMRR SE RLE (%)
50−59vs.<50 0.75 0.0107 0.75* 0.0493 21.3579 0.75* 0.0576 29.2222 0.75* 0.0380 12.6944
60-69 vs. <50 0.88 0.0130 0.88* 0.0600 21.3580 0.88* 0.0599 21.2823 0.87* 0.0486 14.0296
70-79 vs. <50 1.71 0.0235 1.71 0.1086 21.3578 1.71 0.1324 31.7953 1.65 0.1005 18.3181
≥80 vs. <50 3.39 0.0465 3.39 0.2150 21.3579 3.39 0.3159 46.1198 3.15 0.2222 22.8188
Quintiles of deprivation
Q2 vs. Q1 1.05 0.0153 1.05* 0.0705 21.3659 1.05* 0.0747 24.0197 1.05* 0.0626 16.8745
Q3 vs. Q1 1.16 0.0166 1.16 0.0767 21.3711 1.16* 0.0873 27.6612 1.15 0.0687 17.1404
Q4 vs. Q1 1.27 0.0182 1.27 0.0839 21.2723 1.27 0.0934 26.3313 1.27 0.0762 17.5240
Q5 vs. Q1 1.48 0.0218 1.48 0.1007 21.3249 1.48 0.1046 23.0039 1.47 0.0885 16.4928
  1. EMRR Excess mortality rate ratio, NBR Negative binomial regression, PEREM Piecewise exponential regression excess mortality model, RLE Relative loss in efficiency, SE Standard error, *p-value >0.05