Dear list,
I have the following data on 120 industries and I want to find out the parameters (number of workers, recycling, type of industry, etc.) that affect their water consumption over time (I have the water consumption every tertile, total 21 tertiles). The data looks as follows:
Industry No. workers Recycling . . . 1995a 1995b 1995c . . . 2001c
1 10 no 1253 1312 1025 . . . 1450
2 54 yes 4269 3895 5487 . . . 6548
3 5 no 985 854 748 . . . 985
4 20 no 2534 3571 5698 . . . 6123
. . . . . . .
. . . .
. . . .
120 30 no 5261 4523 7853 . . . 8596
I was thinking to perform repeated measures ANOVA (21 repeated measurements) and then adding each one of the parameters step by step if significant. I wanted to ask if this is not the right approach, like if there is a limitation of the number of repeated measures you can analyze. I am aware of time series data analysis but I do not know how to apply it for the above data and that is why I was thinking the repeated measures ANOVA. We will assume that the number of workers and all other parameters did not change over time. Please note that the above data are not real.
I would be grateful for any suggestions or help.
Thank you in advance
Bettina
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