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Two Way Repeated Measures Analysis of Variance (ANOVA)

When this test is selected, you are presented with the list of independent variables. In the above example the IVs are valence (levels are positive and negative) and item format (levels are pictures and words) and the DV in this example is the mean reaction time. Once the variable has been selected, you can then click 'OK' to generate a brief description of the test.

Click the 'Next' button to continue. With a two way ANOVA, there are three analyses to consider: The main effect for each of the two independent variables and the interaction between them. LabWriteUp allows you to enter the data for each of these analyses independently. In this example, we select interaction as the effect we wish to describe. When you do this you click on the two variables (while holding down the 'Ctrl' key on the keyboard) and then click 'Next'. You can then enter details of the interaction:

If you want to produce a textual, graphical, or tabulated description of the summary data, click the 'Enter data for plot, table, or text'. A data grid appears with all four cells of the interaction shown in rows:

As you enter the data, LabWriteUp calculates a suitable maximum value of the Y axis (so that the bars do not protrude above the y axis). However, you can enter a number for this value if you wish it to be different. If you wish to return to this data set later, you can save the data by selecting 'Save this data'.

When these data have been entered, plot the graph, table it, or describe the summary data textually. In this example let us assume that we created an interaction plot for this data (use 'Plot This' to create a plot of the data and 'Table This' to prodcue a table of the data). In this example the description is:

Having created an interaction plot, the text now requires an interpretation of the interaction, namely the precise effect that the two variables have on reaction time.

Next >> Two Way Independent Measures ANOVA

 

This test is used when the data is at least interval, when you are looking to test for differences, and when there are two independent variables, both of which are repeated measures (e.g., all participants are subjected to 2 x 2 = 4 different conditions).