Multiple comparison graphs

Command: Graphs
Next selectMultiple comparison graphs


Allows to visualize the influence of a qualitative (discrete) factor on another (continuous) variable.

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).

Required input

The following need to be entered in the dialog box: for Data select a continuous variable, and for Factor codes a qualitative factor. The qualitative factor may either be character or numeric codes. These codes are used to break-up the data into several subgroups.

When you want to use a continuous variable as the qualitative, discrete factor, you can convert the continuous data by using the Create groups tools.

Multiple comparison graphs

After you have clicked the Drop-down button button you obtain a list of variables. In this list you can select a variable by clicking the variable's name.

Graphs: see Data comparison graphs.

If the data require a logarithmic transformation, select the Logarithmic transformation option.

After you have completed the form, click the OK button to obtain the graph.


Multiple comparison graphs Chart with bars representing the mean age of patients in a multicenter study.
'Error bars' represent 95% confidence intervals.
Multiple comparison graphs Chart with all data points for systolic blood pressure.
'Error bars' represent 95% confidence intervals.
A line connects the mean of the two treatment groups (coded 0 and 1).
Multiple comparison graphs Chart with the evolution of sperm motility during 12 years.
The means for every year are connected by a line.
Error bars represent 95% confidence intervals for the mean.


  • 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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