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I have performed this model:

M1 <- lmer(RNA_V ~ time + GENDER + time:GENDER + (time | PATIENT), df, REML=T)

I need to know if the two genders have different viral decay (relation between time and RNA in a longitudinal dataframe with several RNA inputs and times for each subject.

The results were: lm

Considering that the association with time and RNA is negative (with more time elapsed, less RNA). The gender==2 condition increases the effect of this association 0.07 times? (almost significant p=0.058). So, the gender==2 presented sharper viral decay curve (more negative), am I right?

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The interpretation of the coefficients is as follows:

  • time = -0.16462 denotes how much the average RNA viral load changes (here decreases) with unit of time for subjects with GENDER = 1.
  • GENDER2 = -0.32416 denotes the difference in average RNA viral loads between subjects with GENDER = 2 and GENDER = 1.
  • time:GENDER2 = 0.07643 denotes the difference between subjects with GENDER = 2 and GENDER = 1 in the average change of RNA viral load per unit of time. That is, the average RNA viral load changes with time + time:GENDER2 = - 0.16462 + 0.07643 per unit of time for subjects with GENDER = 2.
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