[R] Coeficients estimation in a repeated measures linear model

Bert Gunter bgunter.4567 at gmail.com
Wed Dec 6 17:41:29 CET 2017


1. You do not have a "repeated measures linear model" .

2. This list is not designed to replace your own efforts to learn the
necessary R background, in this case, factor coding and contrasts in linear
models. I would suggest you spend some time with any of the many fine R
linear model tutorials that can be found on the web. Here is one place to
look for suggestions: https://www.rstudio.com/online-learning/#R  . But
just googling around you'll probably find something that may suit even

3. This list is primarily for R programming help, not statistics help
(although they do sometimes intersect). For the latter, try a statistics
site like stats.stackexchange.com  .

4. Finally, as always, consulting with a local statistical resource, if
available, is always worth considering.



Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Wed, Dec 6, 2017 at 6:17 AM, Sergio PV <serpalma.v at gmail.com> wrote:

> Dear Users,
> I am trying to understand the inner workings of a repeated measures linear
> model. Take for example a situation with 6 individuals sampled twice for
> two conditions (control and treated).
> set.seed(12)
> ctrl <- rnorm(n = 6, mean = 2)
> ttd <- rnorm(n = 6, mean = 10)
> dat <- data.frame(vals = c(ctrl, ttd),
>                   group = c(rep("ctrl", 6), rep("ttd", 6)),
>                   ind = factor(rep(1:6, 2)))
> fit <- lm(vals ~ ind + group, data = dat)
> model.matrix(~ ind + group, data = dat)
> I am puzzled on how the coeficients are calculated. For example, according
> to the model matrix, I thought the intercept would be individual 1 control.
> But that is clearly not the case.
> For the last coeficient, I understand it as the mean of all differences
> between treated vs control at each individual.
> I would greatly appreciate if someone could clarify to me how the
> coefficients in this situation are estimated.
> Thanks
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