# Clustered multiple comparison graphs

Command: | Graphs Clustered multiple comparison graphs |

## Description

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).

## Required input

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.

## Examples

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

## Literature

- 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.