Beginner question.
How do you interpret the coefficients of a mixed model (Multilevel mixed-effects linear regression) when the dependent variable (lnConc) has been logtransformed?
What does the coefficient of the dependent variable (-1,8377) and the independent variables say (Dose: 2,087 T: -0,571 Weight: -0,0838) ?
And if you have know of a webpage, where things like this are explained in simple terms I would love to know.
Thank you!
Code:
mixed lnConc bn.Rand Dose T Weight || ID: Mixed-effects ML regression Number of obs = 411 Group variable: ID Number of groups = 179 Obs per group: min = 1 avg = 2.3 max = 9 Wald chi2(4) = 2.51 Log likelihood = -1853.5324 Prob > chi2 = 0.6424 ------------------------------------------------------------------------------ Conc | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Rand | A | -1.837739 2.37127 -0.78 0.438 -6.485341 2.809864 B | 0 (omitted) | Dose | 2.08743 2.15974 0.97 0.334 -2.145583 6.320443 T | -.0571639 .2980181 -0.19 0.848 -.6412686 .5269407 Weight | -.0838257 .0746945 -1.12 0.262 -.2302242 .0625728 _cons | 64.30447 6.896226 9.32 0.000 50.78811 77.82082 ------------------------------------------------------------------------------ ------------------------------------------------------------------------------ Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval] -----------------------------+------------------------------------------------ ID: Identity | var(_cons) | 40.22586 27.91004 10.32555 156.7102 -----------------------------+------------------------------------------------ var(Residual) | 446.8908 39.04148 376.5637 530.3524 ------------------------------------------------------------------------------ LR test vs. linear model: chibar2(01) = 2.71 Prob >= chibar2 = 0.0499
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