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One-Way Repeated Measures ANOVA

Normal analysis of variance (One-Way and Two-way) requires a sample that follows a normal distribution. However, for repeated measurement, normality of the sample cannot be satisfied, special ANOVA should be used. Repeated measures ANOVA uses analysis of variance to test whether or not the means of two or more matched samples are equal. Origin's ANOVA for repeated measures, both one-way and two-way, are powerful and user-friendly.

  1. Two kinds of input dataset modes, indexed and raw, are supported.
  2. There are eight different methods for customers to do means comparison. They are Tukey, Bonferroni, Dunn-Sidak, Fisher LSD, Scheffe, Dunnett, Holm-Bonferroni and Holm-Sidak.
  3. There are three kinds of plots for customers to choose, including Bar Chart, Means Plot (SE as error) and Means Comparison Plot (only available when means comparison is performed).
  4. Mauchly's test for sphericity is performed, as well as three methods to adjust it: Greenhouse-Geisser Epsilon, Huynh-Feldt Epsilon and Lower-bound Epsilon.

  One Way Repeated Measures ANOVA interface

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Further, customers can decide where to output his/her Report Tables as well as fitted values, etc. Note that repeated measures ANOVA in Origin require balanced data, that is, each level of the factor has the same set of data points.

An illustration of One Way Repeated Measures ANOVA results being displayed in Origin

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Suppose we are interested in whether the effect of a weight loss method will weaken over time. 30 subjects' weight information were recorded 3 times. Their weight loss after adopting this banting for one month, three months and half a year was stored in a worksheet.

The figure above illustrates how One-Way repeated measures ANOVA can be used to analyze the effect of this weight loss method.

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