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Table 3 Goodness-of-fit of the probit-log(dose) regression models calculated from the example data using the ML procedure (Excel), Polo-Plus and SPSS

From: Comparing lethal dose ratios using probit regression with arbitrary slopes

Examples χ 2 h b g c
Excel Polo-Plus SPSS1a SPSS2a Excel Polo-Plus SPSS1a SPSS2a Excel
Rotenone 1.729 1.729 1.729 1.729 0.576 0.576 0.576 0.576 0.050
Deguelin 12.026d 12.026d 12.026d 12.026d 3.006 3.006 3.006 3.006 0.260
Mixture 4.995 4.995 4.995 4.995 1.249 1.249 1.249 1.249 0.043
Fairfax 3.754 3.754 3.754 3.754 1.251 1.251 1.251 1.251 0.071
Schaefer 11.384d 11.384d 11.384d 11.384d 3.795 3.795 3.795 3.795 0.384
Pixley e 2.671 2.708 2.712 0.064 1.335 1.354 1.356 0.032 0.069
BugRes 1.382 1.358 1.362 1.266 0.461 0.453 0.454 0.633 0.094
BugLab 13.555 11.081 27.454 10.181 1.936 1.583 3.922 1.697 0.325
  1. aSPSS includes the natural responses proportion by inputting the value of C, and SPSS calculates the corrected p from the data
  2. bh, heterogeneity factor (see Eq.(17)). SPSS did not give h. To compare the results from this study and Polo-Plus, it was shown as h = χ2/d.f. here
  3. cThe g value was calculated as Eq.(22). Polo-Plus and SPSS did not calculate the g values
  4. dχ2 indicated the goodness-of-fit test was significant at α = 0.05
  5. eBold items indicated the data sets included natural responses