How to catch data from the different dataframes and lm problem?

1) I have a dataframe.  Based on ?formulation? and ?subject?, a
dataframe is split into 4 dataframes.  The
example is as follows.  Moreover, I want
to calculate ?test? value for these 4 dataframes.  My question is 
that the ?test? values not
correct and I do not know where the problem is.

What does the variable "test" represent?  It isn't clear from your code 
what it means.  (Currently it looks like a cumulative rate of change of 
concentration with respect to time; are you really sure you want this?)

2) There are 12 ?test? (y) values from 1).  Then, I want to model 
the relationship
between ?concentration? (X) and ?test? (Y) by fitting the linear 

regression,

such lm(Y~X) and this is my target.  I
think that if I can catch ?test? (Y) values and ?concentration? (X) 
values into
a dataframe, then I can carry out regression.  So, how to catch all 
?test? values from
different dataframes?  Or does anyone
have better way to get this target?

Once you have all your "test" values, you probably want to perform a 
regression on all the data, in a single data frame, with "formulation" and 
"subject" as effects, e.g.
lm(test~concentration+formulation+subject, data=df)

If the subjects are drawn from a large population, it is better to 
represent them as random effects in a mixed effects model.
library(nlme)
lme(test~concentration+formulaion, data=df, random=~1|subject)

Regards,
Richie.

Mathematical Sciences Unit
HSL


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