Skip to contents

Contrast Estimates

Source: R/estimateContrasts.R
estimateContrasts.Rd

Calculates and prints Tukey multiple confidence intervals for contrasts in one or two-way ANOVA.

Usage

estimateContrasts(
  contrast.matrix,
  fit,
  row = TRUE,
  alpha = 0.05,
  L = NULL,
  FUN = identity
)

Arguments

contrast.matrix

A matrix of contrast coefficients. Separate rows of the matrix contain the contrast coefficients for that particular contrast, and a column for each level of the factor.

fit

Output from the [lm()] function.

row

If `TRUE`, and the ANOVA is two-way, then contrasts in the row effects are printed, otherwise contrasts in the column effects are printed. Ignored if the ANOVA is one-way.

alpha

The nominal error rate for the multiple confidence intervals.

L

Number of contrasts. If `NULL`, `L` will be set to the number of rows in the contrast matrix, otherwise `L` will be as specified.

FUN

Optional function to be applied to estimates and confidence intervals. Typically used for back-transformation operations.

Value

Returns a matrix whose rows correspond to the different contrasts being estimated and whose columns correspond to the point estimate of the contrast, the Tukey lower and upper limits of the confidence interval, the unadjusted p-value, and the Tukey and Bonferroni p-values.

Note

Deprecated in s20x 3.4.0. Use the emmeans package instead.

See also

[summary1way()], [summary2way()], [multipleComp()]

Examples

## computer data:
data(computer.df)
computer.df = within(computer.df, {selfassess = factor(selfassess)})
computer.fit = lm(score ~ selfassess, data = computer.df)
contrast.matrix = matrix(c(-1 / 2, -1 / 2, 1), byrow = TRUE, nrow = 1, ncol = 3)
contrast.matrix
#>      [,1] [,2] [,3]
#> [1,] -0.5 -0.5    1
estimateContrasts(contrast.matrix, computer.fit)
#> Warning: estimateContrasts() is deprecated; use the emmeans package instead.
#>            Estimate Tukey.L Tukey.U Tukey.p
#> Contrast 1 39.07143 18.5861 59.5568   4e-04