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How to: Two-way ANOVA |
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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 won't 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 explains how to do ordinary two-way ANOVA. If you want to do repeated measures two-way ANOVA see separate examples for repeated measures by row and repeated measures by column. 1. Create a data table From the Welcome (or New Data Table and Graph) dialog, choose the Grouped tab. Entering raw data If you are not ready to enter your own data, chose to use sample data and choose: Two-way ANOVA -- Ordinary. If you plan to enter your own data, it is important that you choose the subcolumn format correctly, for the maximum number of replicates you have. Leave the graph set to its default -- interleaved bars, vertical. Entering averaged data If you have already averaged your replicates in another program, you can choose (at the bottom of the dialog) to enter and plot the mean and SD (or SEM) and N. 2. Enter data Here are the sample data:
Note that one value is blank. It is fine to have some missing values, but you must have at least one value in each row for each data set. The following table cannot be analyzed by two-way ANOVA because there are no data for treated women. But it doesn't matter much that there are only two (not three) replicates for control men and treated men.
If you are entering mean, SD (or SEM) and N, You must enter N (number of replicates) but it is ok if N is not always the same.
3. Choose two-way ANOVA
5. Interpret the results Interpreting results: Two-way ANOVA Graphing tips: Two-way ANOVA data |