The Longitudinal Trial

Statistical analysis in a longitudinal trial involving subject sacrifice?

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In order to measure your outcome, the animal needs to be sacrificed and so each animal can only be measured once.  In this case, you do not have repeated measures as each animal is measured only once.  The time effect would refer to the number of weeks of exposure the animal receives.  You could use a one-way ANOVA (assuming normality within times and that Welch’s F-test or similar is used if there are unequal variances between times, possibly following an appropriate transformation) or Kruskal-Wallis test to compare a continuous outcome between the times with post-hoc tests to compare individual times (note that Dunnett’s test would be useful if you wanted to adjust for multiple comparisons and are not interested in all possible comparisons, just those between control and each time).  If there are many times, you might be interested in modelling time as a continuous predictor (linear or non-linear) of the outcome.

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