I am estimating, for example, the following double-difference / difference-in-difference logistic regression where opt_dum, depstat (Mild or None), and treat (HT or Con) are all binary variables.
The output of the model is as follows:
Code:
logit opt_dum i.depstat##i.treat, or Iteration 0: log likelihood = -166.14693 Iteration 1: log likelihood = -121.37891 Iteration 2: log likelihood = -120.88007 Iteration 3: log likelihood = -120.87909 Iteration 4: log likelihood = -120.87909 Logistic regression Number of obs = 240 LR chi2(3) = 90.54 Prob > chi2 = 0.0000 Log likelihood = -120.87909 Pseudo R2 = 0.2725 ------------------------------------------------------------------------------- opt_dum | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- depstat | Mild | .3891403 .1851221 -1.98 0.047 .1531694 .9886448 | treat | HT | 19.15126 9.456233 5.98 0.000 7.276179 50.40706 | depstat#treat | Mild#HT | .5459965 .3697249 -0.89 0.372 .1448083 2.058668 | _cons | .3953488 .1132654 -3.24 0.001 .2254839 .693179 -------------------------------------------------------------------------------
Code:
. margins i.depstat##i.treat, post coeflegend Predictive margins Number of obs = 240 Model VCE : OIM Expression : Pr(opt_dum), predict() ------------------------------------------------------------------------------- | Margin Legend --------------+---------------------------------------------------------------- depstat | Non | .5833333 _b[1bn.depstat] Mild | .375 _b[2.depstat] | treat | Con | .2083333 _b[1bn.treat] HT | .75 _b[2.treat] | depstat#treat | Non#Con | .2833333 _b[1bn.depstat#1bn.treat] Non#HT | .8833333 _b[1bn.depstat#2.treat] Mild#Con | .1333333 _b[2.depstat#1bn.treat] Mild#HT | .6166667 _b[2.depstat#2.treat] -------------------------------------------------------------------------------
Code:
. lincom ( _b[2.depstat#2.treat]- _b[2.depstat#1bn.treat])-(_b[1bn.depstat#2.treat]-_b[1bn.depstat#1bn.treat]) ( 1) 1bn.depstat#1bn.treat - 1bn.depstat#2.treat - 2.depstat#1bn.treat + 2.depstat#2.treat = 0 ------------------------------------------------------------------------------ | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- (1) | -.1166667 .1047263 -1.11 0.265 -.3219264 .0885931 ------------------------------------------------------------------------------
Caroline
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