## RCB repeated in timeDepending upon the specific effect of time, either split-plot or regression analyses could be appropriate for these experiments. However, advances in statistics and computer applications allow the researcher to further explore the effect of time and insure that the appropriate hypotheses are tested. Other designs (such as CRD or Latin) can also be repeated in time, but are not included at this time in the field guide.
- Multiple measurements of the same experimental subjects are made in time.
- Treatments are assigned at random within blocks of adjacent subjects, each treatment once per block.
- The number of blocks is the number of replications.
First Block I A B C D E F Block II F A E B D C Block III C B F A D E Second Block I A B C D E F Block II F A E B D C Block III C B F A D E Third Block I A B C D E F Block II F A E B D C Block III C B F A D E
The appropriate table format will depend upon the analysis and the effect of time. The following takes it as a more traditional split-plot in time and assumes that there is no more correlation between samples taken closer in time than those taken further apart in time. The SAS System provides tests for this assumption.
PROC GLM; CLASS BLOCKS TREAT; MODEL TIME1 TIME2 TIME3 = BLOCKS TREAT; REPEATED TIME /PRINTE; RUN; Note: the PRINTE options produces tests for assumptions concerning time.
- Two-way Factorial arrangement on a RCB assigned treatments are combinations of treatments from two sets
- Split Plot on a RCB: one set of treatments is assigned at random to experimental units; a second set is assigned to at random to sub-units.
- Split-block design: one set of treatments is randomized in one directios; a second set is randomized in a second direction.
- Regression--comparing trends from different treatments: a set of treatments from a quantitative range are crossed on treatments from a qualitative set.
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