I have read about the topic and I was wondering if anybody could help me to interpret the following description of repeated measurements I found in a manuscript (very detailed but still confuse in my point of view):
"Year, location, rotation type, late-season input treatment, cultivar MG nested within the location, cultivar nested within MG and location, and their interactions were considered as fixed factors in the model. To simplify field operations of cover crop planting and termination, the rotation type was randomized within two sections in the field (lots) and each lot was then split into two blocks. Lot, which was nested within year and location, and block, which was nested within lot, and their interactions with other fixed effects were considered as random factors. The effect of rotation type and late-season input treatment on the variables measured was analyzed by generating the least significant differences for the highest level interaction with these fixed effects that was significant at P < 0.05".
I would appreciate your help/thoughts on it
Thank you!
LM
A typical example for a botched experiment which did obviously not start with a clear scientific hypothesis: the objective of ANOVA is mainly to check if your hypothesis is correct or not, just a simple yes or no! All this interaction stuff is a "trick" to minimize the residual error. This experiments are often designed by persons without a clue on biological processes and end up with the proverbial "reading the tea leaves"
Repeated measures ANOVA : To interpret the results of an ANOVA you must first calculate the F-score.
The F value is a measure of the difference between the means of the groups.
If the F value is significant, it means that there is a significant difference between the group means.
The significance level is generally defined as 0.05 or 0.01.
If the F-value is not significant, it means that there is no significant difference between the group means.
- Badges
- Science topic