Reading for January 8

1. (Paper 1) I notice that in the table of simulated data, the values of X of each subject are randomly assigned. However, in reality, the repeated measurements on the same subject should be similar, which decreases the variability within subject. Will it affect the conclusion to the example?

2. (Paper 3) In the second paragraph, the author said that if subjects with hypertension were measured again, the mean would be closer to the whole population, even if they are not treated. But I think the difference can also become greater than before. If not, after several times of re-measurements, the mean of extreme ones will be very close to the population mean.

3. (Paper 4) In the last but one paragraph, the author mentioned that when the correlation is high (say r>0.8), analysis of change scores is a reasonable alternative. So what happens when the correlation is low (say r<0.2)? Will analysis of follow up be an alternative?