Multiple comparison graphs

Command:    

Graphs
Next selectMultiple comparison graphs

Description

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.

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.

Examples

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

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.

See also

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