I have a data set which is outlined in the table below:

\(

\begin{tabular}{|l|cr|}

\hline

ID & baseline & response \\

\hline

1 & $x_1$ & $y_1$ \\

1 & $x_2$ & $y_2$ \\

1 & $x_3$ & $y_3$ \\

1 & $x_4$ & $y_4$ \\

2 & $x_5$ & $y_5$ \\

2 & $x_6$ & $y_6$ \\

2 & $x_7$ & $y_7$ \\

3 & $\cdots$ & $\cdots$ \\

\hline

\end{tabular}

\)

The data consists of 4 different ID's (4 different humans), and each human has had a baseline recording (\( x \)) and a response recording (\( y \)) taken about 3 times (this varies from human to human). I want to compare the means \( \bar{x} \) and \( \bar{y} \), whilst controlling for the fact that I have a repeated measures, and 3-4 recordings for each human.

I have tried comparing weight means, but this doesnt account for the fact that I have 4 different people. How would I analyse this data, given the low number of recordings (approximately \( n=14 \) in total).

I think the best idea would be to do a 2-way repeated measures ANOVA, with one of the independent variables being the human ID, taking values 1-4. What do you guys think?

:tup::yup::tup: Thanks for your help!!! :tup::yup::tup: