One-way analysis of variance

Command:

Statistics Anova One-way analysis of variance

Description

One-way analysis of variance is used to test the difference between the means of several subgroups of a variable (multiple testing).

How to enter data

The following figure illustrates how data need to be entered. For Anova, you need one continuous variable (concentration) and one qualitative variable (grade). The data for each case are entered on one row of the spreadsheet.

The qualitative factor may either be character or numeric codes. These codes are used to break-up the data into several subgroups for the Anova procedure, to calculate the Between groups and Within groups variation.

Required input

For Data, select a continuous variable, and for Factor codes the qualitative factor.

Options

Logarithmic transformation: if the data require a logarithmic transformation, select the Logarithmic transformation option.

Results

Levene's Test for Equality of Variances

Prior to the Anova test, Levene's Test for Equality of Variances is performed. If the Levene test is positive (P<0.05) then the variances in the different groups are different (the groups are not homogeneous) and you may need to apply a logarithmic transformation to the data, or use a non-parametric statistic.

Anova

The results of the ANOVA are presented in an ANOVA table, followed by the F statistic and associated P value. If the P value is less than 0.05, then you can accept the hypothesis that the means of at least two of the subgroups differ significantly.

Student-Newman-Keuls post-hoc test

If the Anova test is positive (P<0.05) then MedCalc performs a Student-Newman-Keuls test for pairwise comparison of subgroups.

Log transformation

If you selected the Log transformation option, the program performs the calculations on the logarithms of the dependent variable, but the different means are back-transformed and reported as the geometric means.

Graph

For a graphical representation of this test, refer to Multiple comparison graphs.

Literature

• Altman DG (1991) Practical statistics for medical research. London: Chapman and Hall.
• Armitage P, Berry G, Matthews JNS (2002) Statistical methods in medical research. 4th ed. Blackwell Science.
• Sheskin DJ (2004) Handbook of parametric and nonparametric statistical procedures. 3rd ed. Boca Raton: Chapman & Hall /CRC.
• Snedecor GW, Cochran WG (1989) Statistical methods, 8th edition. Ames, Iowa: Iowa State University Press.

See also

• Two-way analysis of variance
• Analysis of covariance
• Repeated measures analysis of variance
• Kruskal-Wallis test
• Friedman test