What is split plot Anova?

What is split plot Anova?

In statistics, a mixed-design analysis of variance model, also known as a split-plot ANOVA, is used to test for differences between two or more independent groups whilst subjecting participants to repeated measures.

What is split plot design and give example?

A typical example of a split-plot design in agriculture is an experiment for investigating the effect of different fertilizers and varieties on the yield of crops. Because these fertilizers are often sprayed from planes, a whole plot of land must be treated with the same type of fertilizer.

When can we use split plot Anova?

You should use the Split Plot ANOVA when you have two or more grouping variables. For instance, if we have recovery data for both a treatment and control group at 3 or more points in time, then treatment/control is the grouping variable and a split plot ANOVA is a suitable analysis.

Why do we use split-plot design?

The split-plot design is used to analyze descriptive data when applying Analysis of Variance (ANOVA). This design tests significant differences among samples and also estimates variation due to panelist inconsistencies3.

What makes a split-plot design different than a factorial design with blocking?

The layout of a split-plot design resembles that of a randomized block design. The key difference between split-plot designs and randomized block designs is that, in randomized block designs, the factor level combinations are randomly assigned to the experimental units in the blocks.

How many errors are involved in split plot?

Since the split-plot design has two levels of experimental units, the whole plot and subplot portions have separate experimental errors2.

Which is for an effect that is tested in split-plot ANOVA?

In a split-plot ANOVA there will be a main effect for groups, a main effect for time, and an interaction between group and time. 29. In a split-plot ANOVA there will be a main effect for groups, a main effect for time, and an interaction between group and time.