# anova2

Two-way analysis of variance

## Syntax

## Description

`anova2`

performs two-way analysis
of variance (ANOVA) with balanced designs. To perform two-way ANOVA
with unbalanced designs, see `anovan`

.

returns
the `p`

= anova2(`y`

,`reps`

)*p*-values for a balanced two-way ANOVA for comparing
the means of two or more columns and two or more rows of the observations
in `y`

.

`reps`

is the number of replicates for each
combination of factor groups, which must be constant, indicating a
balanced design. For unbalanced designs, use `anovan`

.
The `anova2`

function tests the main effects for
column and row factors and their interaction effect. To test the interaction
effect, `reps`

must be greater than 1.

`anova2`

also displays the standard ANOVA
table.

enables the ANOVA table display when `p`

= anova2(`y`

,`reps`

,`displayopt`

)`displayopt`

is `'on'`

(default)
and suppresses the display when `displayopt`

is `'off'`

.

`[`

returns a `p`

,`tbl`

,`stats`

]
= anova2(___)`stats`

structure,
which you can use to perform a multiple comparison test. A multiple
comparison test enables you to determine which pairs of group means
are significantly different. To perform this test, use `multcompare`

, providing the `stats`

structure
as input.

## Examples

## Input Arguments

## Output Arguments

## Alternative Functionality

Instead of using `anova2`

, you can create an `anova`

object by using the `anova`

function.
The `anova`

function provides these advantages:

The

`anova`

function allows you to specify the ANOVA model type, sum of squares type, and factors to treat as categorical.`anova`

also supports table predictor and response input arguments.In addition to the outputs returned by

`anova2`

, the properties of the`anova`

object contain the following:ANOVA model formula

Fitted ANOVA model coefficients

Residuals

Factors and response data

The

`anova`

object functions allow you to conduct further analysis after fitting the`anova`

object. For example, you can create an interactive plot of multiple comparisons of means for the ANOVA, get the mean response estimates for each value of a factor, and calculate the variance component estimates.

## References

[1] Hogg, R. V., and J. Ledolter. *Engineering
Statistics*. New York: MacMillan, 1987.

## Version History

**Introduced before R2006a**

## See Also

`anova`

| `anova1`

| `anovan`

| `multcompare`