I know that in split plot design the main plot error is larger than the sub plot error. There is more error degree of freedom for sub plot as compared to main plot.
But, in statistical analysis, if 50% characters having higher error mean square for the main plot error and smaller error mean square for the sub plot error. And the remaining 50% characters showing smaller error mean square for the main plot error and higher error mean square for the sub plot error in the ANOVA of split plot design.
So, the analysis is statistically correct or not ?
Hello Ravindra,
Main plot "error" is derived from plot to plot differences (e.g., between cases or
"subjects"), whereas subplot "error" comes from variation within plots, which tends to be smaller. This is because the within-plot scores tend to be correlated, for one reason, and because plot to plot differences are separated out of the computation of that variation.
It's no different than the explanation of why the standard error for an independent groups t-test tends to be larger than the standard error for a dependent t-test.
Good luck with your work.
Hello Ravindra,
Main plot "error" is derived from plot to plot differences (e.g., between cases or
"subjects"), whereas subplot "error" comes from variation within plots, which tends to be smaller. This is because the within-plot scores tend to be correlated, for one reason, and because plot to plot differences are separated out of the computation of that variation.
It's no different than the explanation of why the standard error for an independent groups t-test tends to be larger than the standard error for a dependent t-test.
Good luck with your work.
The main plot always exposes to a larger area compared to the subplot. larger the area more the chance of error and vice-versa. also, the main plot error degree of freedom always less compared to the subplot. so error means sum of the square of the main plot always more compares to the subplot.
Thank you David Morse sir and Naveena K . sir for your kind guidance.
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