EpiData provides the conditional maximum likelihood estimate for OR, which is normally accepted as a better estimate.
If you put your data into OpenEpi you can see the differences between estimates and confidence intervals:
Jamie
epidata-list@lists.umanitoba.ca wrote:
This is concerning to v2.0.3.129 EpiData Analysis. Recently I dig in to OR and RR using said version. The data base I used was one used in SPSS to do the same. In essence, the calculation result were different from what I obtained from SPSS, given that I recoded outcomes and risk exposures, i.e. 1=2, 2=1. (SPSS uses ascending order for both outcomes and risk exposures, 1 codes as positive 2 as negative which is just the opposite of EpiData Analysis handling) EpiData Analysis result: OR=3.68 (95% CI: 1.03-11.89)Fishersexact p= 0.0224 SPSS result: OR=3.72 (3.7158) (95% CI: 1.27039-10.86604) Fishersexact p=.02239 Whereas RR resulted the same. EpiData Analysis: RR = 2.86 (95% CI: 1.31-6.24)Fishersexact p= 0.0224 SPSS: RR = 2.86 (2.85789) (95% CI: 1.30965-6.23646) USING CELL OBSERVED FREQUENCIES AS A=6, B=13, C=20, D=161 WHEREAS A:C1R1, B:C2R1, C:C1R2, D:C2R2. I wonder if the formula used by EpiData Analysis is OR=(A/C)/(B/D)=(A/B)/(C/D)= (AD)/(BC). The OR as well as corresponding CI are different from that of SPSS