Yannan Jiang wrote:> Hi there,
>
>
>
> I am trying to run simulations using R with linear mixed model (lme). There
> are two factors in my fixed effect model, educ (treatment and control) and
> mth (visit 1, 2, and 3). What I want to obtain is the estimated treatment
> difference (treatment - control) at visit 3, plus the standard error and
> p-value. This can be easily obtained in SAS using lsmeans or estimate
> statements, but I am not sure how to do this in R.
>
>
>
> The fixed effects I obtained are as follows:
>
>
>
> Fixed effects: ymth ~ educ * mth - 1
>
> Value Std.Error
> DF t-value p-value
>
> educcont 0.14814308 0.006232419 93
> 23.769758 0.0000
>
> eductreat 0.13696952 0.006255672 93
> 21.895254 0.0000
>
> mthymth2 0.00003759 0.006333043 165
> 0.005936 0.9953
>
> mthymth3 0.01075489 0.006251328 165
> 1.720416 0.0872
>
> eductreat:mthymth2 0.00323847 0.008947291 165
> 0.361950 0.7179
>
> eductreat:mthymth3 -0.01246565 0.008941306 165
> -1.394164 0.1651
>
>
>
>
>
> The estimated treatment difference I am interested are:
>
>
>
> a<-0.14814308+0.01075489
>
> b<-0.13696952+0.01075489-0.01246565
>
>> b-a
>
> [1] -0.02363921 (treatment effect at visit 3, same as SAS lsmean output)
>
>
>
> But I don't know how to get the standard error and corresponding
p-value for
> this estimate. Any of your helps on that would be greatly appreciated!
How about fitting the model this way?
df$mth <- relevel(df$mth, ref = "ymth3")
lme(ymth ~ educ * mth, random = ~ 1 | id, data = df)
The coefficient for educ will contain the simple effect of educ at
mth=ymth3, along with a standard error and p-value.
> Thanks,
>
> Yannan
>
>
>
>
> [[alternative HTML version deleted]]
>
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