Clustered multiple comparison graphs

Command: Graphs
Next selectClustered multiple comparison graphs


Allows to visualize the influence of two categorical variables on another (continuous) variable.

The categorical variables may contain character or numeric codes. These codes are used to break-up the data into different subgroups.

The graph can be composed from different elements: Bars, Horizontal lines, Markers and or Connecting lines for mean or median, with choice of different error bars for mean (95% CI, 1 SEM, 1 SD, 2 SD, 3 SD, range) or median (95% CI, 25-75 percentiles, 10-90 percentiles, 5-95 percentiles, 2.5-97.5 percentiles, 1-99 percentiles, range), Box-and-whisker plot (Tukey, 1977) or Notched box-and-whisker plot (McGill et al., 1978), and/or Dot plot (display all data) (for a see full description see Data comparison graphs).

How to enter data

You need to enter data for one continuous variable (MEASUREMENT1 in the example) and 2 categorical variables (GENDER and TREATMENT in the example).

Clustered multiple comparison graphs

Required input

Clustered multiple comparison graphs

The following need to be entered in the dialog box:

  • Data: a continuous variable that will be represented in the graph;
  • Factor codes: a categorical variable that contains codes to break-up the data into subgroups.
  • Define clusters by factor: a second categorical variable to make a second subdivision in the subgroups.
  • Select: a filter to include only a selected subgroup of cases in the graph.
  • Graphs: see Data comparison graphs.
  • Options: if the data require a logarithmic transformation, then select the Logarithmic transformation option.


Clustered multiple comparison graphs

This is an example of a graph with option "Dots" selected:

Clustered multiple comparison graphs


  • Altman DG (1991) Practical statistics for medical research. London: Chapman and Hall.
  • McGill R, Tukey JW, Larsen WA (1978) Variations of box plots. The American Statistician, 32, 12-16.
  • Tukey JW (1977) Exploratory data analysis. Reading, Mass: Addison-Wesley Publishing Company.

See also

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