How to: Two-way ANOVA. Repeated measures by column

Two-way ANOVA, also called two-factor ANOVA, determines how a response is affected by two factors. For example, you might measure a response to three different drugs in both men and women. Drug treatment is one factor and gender is the other.

Prism uses a unique way to enter data. You use rows and columns to designate the different groups (levels) of each factor. Each data set (column) represents a different level of one factor, and each row represents a different level of the other factor. You need to decide which factor is defined by rows, and which by columns. Your choice will not affect the ANOVA results, but the choice is important as it affects the appearance of graphs and the kinds of post tests Prism can compare.

This page shows you how to enter and analyze data with repeated measurements placed in a subcolumn. Use a different 'how to' page if you enter repeated measurements in a row.

1. Create a data table and enter data

From the Welcome (or New Data Table and Graph) dialog, choose the Grouped tab.

If you are not ready to enter your own data, chose to use sample data and choose: Two-way ANOVA data -- RM by columns. ("RM" means Repeated Measures).

If you plan to enter your own data, it is important that you choose the subcolumn format correctly, for the maximum number of subjects you have with any treatment.

Since your data are repeated measures, you want to make a graph that shows that. Choose the second choice on the second row of graph types, so values are connected properly on the graph. Choose to plot each replicate, connecting each subcolumn. If you choose the sample data, Prism will automatically choose the appropriate graph.

Arrange your data so the data sets (columns) represent different levels of one factor, and different rows represent different levels of the other factor. The sample data set compares five time points in two subjects under control conditions and two after treatment. 

Each subcolumn (one is marked with a red arrow above) represents repeated measurements on a single subject.

Missing values

It is OK if some treatments have more subjects than others. In this case, some subcolumns will be entirely blank. But you must enter a measurement for each row for each subject. Prism cannot handle missing measurements with repeated measures ANOVA.

2. Choose two-way ANOVA

1.	From the data table, click on the toolbar.

Also, choose post tests if they will help you interpret your results, and enter the name of the factors that define columns and rows.

3. Interpret the results

Interpreting results: Repeated measures two-way ANOVA

Graphing tips: Repeated measures two-way ANOVA

Checklist: Repeated measures two-way ANOVA