plotting statistical results

Commands: emegs2d, emegs3d

There are mainly two different types of statistical results you can visualize using EMEGS: cell means of a single ANOVA and continuous results in form of SCADS files.

files: Visualizing results of continuous analysis works pretty much like creating 3d plots of scalp potentials or magnetic fields or other continuous signals. However, for files containing p-Values, EMEGS offers a special coloring that reminds of significance color coding used in fMRI research: reddish colours stand for a significant positive difference, blueish colours code a significant negative difference. However, this only applies to t-statistics, the test parameter of which still contain directional information. ANOVA-results are F-statistics and do not contain directional information. Therefore, p-value-files generated by the ANOVA module contain only positive p-values and therefore will always be in reddish colours. To activate statistical colouring, click the 'Stats' button on the emegs3d-menu ...


Figure 1: statistical coloring controls

and then select the significance level with the neighbouring widgets. For alpha-levels of 0.1,  0.05 and 0.01, there are shortcut-buttons available ('90', '95' and '99'). If you wish to set a different level, type in the desired level as percentage in the edit box on the right of the default buttons (e.g. '99.9' for alpha<0.001). After this, you are ready to create statistical plot using all the 3d plotting formats available in emegs3d. Nonsignificant values will be displayed in white (they appear invisible), while significant values will recieve strong colouring. Please note, that the default behavior of emegs3d is to average across different sample points, if you are plotting intervalls larger than one sample point. However, in the case of colour coded p-values, this can  easily lead to entirely empty plots, as all (averaged) values are below the threshold. A solution to this is to either set a considerably low alpha level, or to avoid the averaging by displaying every sample point in the dataset separately.


       Example of statistical plotting and significance colour coding

Cell means of a single ANOVA: For the first type, one is usually interested in average values of cells (for instance as bar plot) and measures of the variance in this cell (error bars). To start the plotting module that allows you to create this kind of plot, choose  \graph\cellplot on the figure displaying the ANOVA results. The window will expand to include a plotting axes and an additional menubar will open that allows you to specify the type of effect and the type of plot you wish to create. You can choose the way the means are displayed (bars, 3dbars or symbols in customizable size), the type of error bar to be used, the labeling of the cells, the polartiy (negative or positive up) and the plotting of the subject values that contribute to the mean in each cell.  On the 'ANOVA-plotting'-menubar, you also have a small graph of the channel groups used for the current analysis.

To plot the cell means corresponding a main effect or interaction, select the components of the desired effect in the dropdownmenu on the ANOVA-plotting panel and click 'add' to add this component to the graph. The name of the component will be added to the axes title, and the cell means will be displayed as bars (default). Clicking 'remove' removes the selected component from the plot. Please note that the order in which you add the components to the plot will determine the grouping of the bars/symbols and their coloring: The first selected component will always stay the topmost grouping criterion. All bars/symbols in one cell of this first component will all have the same color.



       Screenshot of the ANOVA plotting module