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

[Richard.Cotton at hsl.gov.uk]

> 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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