Linear Mixed Model, a Regression type Statistical Analysis or other?

relliott

New Member
I have performed a study on stability where my outcome is continuous and the two inputs are ordinal. Essentially:

I am trying to understand if the weight location in a backpack (high, medium, low) and the grade of the road (0%, 5% and 10%) are related to significant differences in stability, which is my continuous outcome measure.
I have 13 participants with full data.
Each person has 9 data points See example below:

Person 1 High Weight, 0 grade, stability #
Person 1 High Weight, 5 grade, stability #
Person 1 High Weight, 10 grade, stability #
Person 1 Medium Weight, 0 grade, stability #
Person 1 Medium Weight, 5 grade, stability #
Person 1 Medium Weight, 10 grade, stability #
Person 1 Low Weight, 0 grade, stability #
Person 1 Low Weight, 5 grade, stability #
Person 1 Low Weight, 10 grade, stability #

Same data for each of 13 participants.

I need suggestions for the best analysis to use to answer my research question. This has applications in military and other fields where people need to carry weight in a backpack and work on uneven ground.

One effort used a Linear Mixed Model, but I suspect it is invalid because it is related to Linear Regression which does not allow a continuous dependent variable. Which option with this few number of participants provide the best determination of stability (a calculated number from measurements taken) for backpack location at each of the slopes given?