I am currently conducting a study using a photothrombotic stroke model in C57BL6 mice and measuring motor function outcome following strokes to determine if a pharmacological treatment can help improve their motor recovery. To measure motor recovery, I am using the tapered beam task and the grid walk task. Both of these tasks measure the number of errors that the mice make during trials. One thing that I've noticed is that a handful of the mice in the placebo group (no pharmacological treatment, just saline) are unable to complete the tasks on the first day of behavior due to the severity of the injury and the lack of treatment.
As such, I'm wondering if there is a standard way to handle missing data that is a result of severe injuries and is important for accurately reflecting differences between my groups. The methods that I can think of would either be filling with the mean for the group, filling with the highest number of errors of the group (e.g. the worst recorded score was 93 errors in the placebo group, presumably the mice unable to complete the task have more severe strokes and should receive the max number of errors observed), or multiple imputation using the MICE package in R. My understanding is that multiple imputation is the standard for filling in data that is not missing at random, but I want to ensure that is true in this scenario as well. Any citations (especially those specific to animal models) to support these methods would be greatly appreciated as well.
A few questions: 1. are the mice "pre-trained to an established baseline" prior to injury? 2. If so, are there any "qualitative scores" of ambulation? 3. are the mice able to do any part of the task, or simply fail immediately? 4. finally, do they recover in the subsequent days, post injury i.e. repeated task on day 2, 3,4...?
If the mice are trained well before the insult, to a zero or close to zero error standard, any animal that can't perform would be maximal error (which could be set as the max time for the task, ie 60sec to traverse the beam is the length of the task). Piloting, as suggested, may also be helpful if you pilot the number of errors on day 1 for untreated controls finding the upper threshold to set a true failure limit. The scoring should have a wide enough range to accommodate for total failure and complete success. Bracketing the score may be in order as well, (0-2 foot slips is perfect vs 3-10 foot slips are mildly impaired...etc). In this manner the repeated measures ANOVA Group (mean score) X Day stats would show deficit and improvement significance. You can assign each bracket a score number.
It appears by your question you only have a few missing day 1 data points in the non-treated injured mice. So long as the injury is standard across all groups and repeatable it should be fine to set "failure limits." Furthermore, we don't want to eliminate mice that fail to perform but spontaneously recover eventually. Titrating the injury too much can also have unintended consequences, ending up with no significant treatment effects.
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