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Added a reference article on impact of unequal group variance for one-way anova
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Isabella Ghement
Isabella Ghement
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Are you dealing with one-way ANOVA, where you woud relate a single factor to an outcome variable? If the variability of the data in each category of your factor is non-constant, that would invalidate both your global ANOVA p-value and your multiplicity-adjusted post-hoc p-values. To trust any of those p-values, you would either want to transform the outcome variable data to stabilize the variance or apply an ANOVA method which can handle non-constancy of variance. See https://pdfs.semanticscholar.org/2d90/7e90e401010d46898b5efd8919ebdec0788c.pdf.

Only if your multiple comparisons were pre-planned could you ignore the global ANOVA p-value (but even then you would want to make sure the data verify the assumptions underlying the ANOVA analysis).

Whether or not you would bother with the global ANOVA p-value therefore depends on whether or not your multiple comparisons were pre-planned. If they were, you could ignore the global ANOVA p-value. If they were not, you couldn't. The age of computers has nothing to do with it, really.

Are you dealing with one-way ANOVA, where you woud relate a single factor to an outcome variable? If the variability of the data in each category of your factor is non-constant, that would invalidate both your global ANOVA p-value and your multiplicity-adjusted post-hoc p-values. To trust any of those p-values, you would either want to transform the outcome variable data to stabilize the variance or apply an ANOVA method which can handle non-constancy of variance.

Only if your multiple comparisons were pre-planned could you ignore the global ANOVA p-value (but even then you would want to make sure the data verify the assumptions underlying the ANOVA analysis).

Whether or not you would bother with the ANOVA p-value therefore depends on whether or not your multiple comparisons were pre-planned. If they were, you could ignore the global ANOVA p-value. If they were not, you couldn't. The age of computers has nothing to do with it, really.

Are you dealing with one-way ANOVA, where you woud relate a single factor to an outcome variable? If the variability of the data in each category of your factor is non-constant, that would invalidate both your global ANOVA p-value and your multiplicity-adjusted post-hoc p-values. To trust any of those p-values, you would either want to transform the outcome variable data to stabilize the variance or apply an ANOVA method which can handle non-constancy of variance. See https://pdfs.semanticscholar.org/2d90/7e90e401010d46898b5efd8919ebdec0788c.pdf.

Only if your multiple comparisons were pre-planned could you ignore the global ANOVA p-value (but even then you would want to make sure the data verify the assumptions underlying the ANOVA analysis).

Whether or not you would bother with the global ANOVA p-value therefore depends on whether or not your multiple comparisons were pre-planned. If they were, you could ignore the global ANOVA p-value. If they were not, you couldn't. The age of computers has nothing to do with it, really.

Source Link
Isabella Ghement
Isabella Ghement
  • 20.9k
  • 2
  • 37
  • 60

Are you dealing with one-way ANOVA, where you woud relate a single factor to an outcome variable? If the variability of the data in each category of your factor is non-constant, that would invalidate both your global ANOVA p-value and your multiplicity-adjusted post-hoc p-values. To trust any of those p-values, you would either want to transform the outcome variable data to stabilize the variance or apply an ANOVA method which can handle non-constancy of variance.

Only if your multiple comparisons were pre-planned could you ignore the global ANOVA p-value (but even then you would want to make sure the data verify the assumptions underlying the ANOVA analysis).

Whether or not you would bother with the ANOVA p-value therefore depends on whether or not your multiple comparisons were pre-planned. If they were, you could ignore the global ANOVA p-value. If they were not, you couldn't. The age of computers has nothing to do with it, really.