Creates a summary object that produces detailed output when printed, including the full ANOVA table, parameter estimates, estimated marginal means, and Levene's test.
Usage
# S3 method for class 'ancova'
summary(
object,
between_subjects = TRUE,
parameter_estimates = TRUE,
marginal_means = TRUE,
levene_test = TRUE,
digits = 3,
...
)Arguments
- object
An
ancovaresult object.- between_subjects
Logical. Show the ANOVA table? (Default: TRUE)
- parameter_estimates
Logical. Show parameter estimates? (Default: TRUE)
- marginal_means
Logical. Show estimated marginal means? (Default: TRUE)
- levene_test
Logical. Show Levene's test? (Default: TRUE)
- digits
Number of decimal places for formatting (Default: 3).
- ...
Additional arguments (not used).
See also
ancova for the main analysis function.
Examples
result <- ancova(survey_data, dv = life_satisfaction, between = gender, covariate = age)
summary(result)
#> ANCOVA (One-Way ANCOVA) Results
#> -------------------------------
#>
#> - Dependent variable: life_satisfaction
#> - Factor(s): gender
#> - Covariate(s): age
#> - Sum of squares: Type III
#> - N (complete cases): 2421
#> - Missing: 79
#>
#> Tests of Between-Subjects Effects
#> ------------------------------------------------------------------------------------------------------
#> Source Type III Sum of Squares df Mean Square F Sig Partial Eta Squared
#> ------------------------------------------------------------------------------------------------------
#> Corrected Model 4.071 2 2.036 1.532 .216 0.001
#> Intercept 3410.020 1 3410.020 2565.986 <.001 0.515 ***
#> age 2.691 1 2.691 2.025 .155 0.001
#> gender 1.418 1 1.418 1.067 .302 0.000
#> Error 3213.356 2418 1.329
#> Total 35088.000 2421
#> Corrected Total 3217.428 2420
#> ------------------------------------------------------------------------------------------------------
#> R Squared = 0.001 (Adjusted R Squared = 0.000)
#>
#> Parameter Estimates
#> ---------------------------------------------------------------------------------------------------
#> Parameter B Std. Error t Sig 95% CI Lower 95% CI Upper Partial Eta Squared
#> ---------------------------------------------------------------------------------------------------
#> Intercept 3.750 0.077 48.670 <.001 3.599 3.902 0.495
#> age -0.002 0.001 -1.423 .155 -0.005 0.001 0.001
#> [gender=Male] -0.048 0.047 -1.033 .302 -0.140 0.044 0.000
#> [gender=Female] 0 (a)
#> ---------------------------------------------------------------------------------------------------
#> (a) This parameter is set to zero because it is redundant (SPSS coding: the
#> last category of each factor is the reference).
#>
#> Estimated Marginal Means
#> (Evaluated at covariate means)
#> -----------------------------------------------------
#> gender Mean Std. Error 95% CI Lower 95% CI Upper
#> -----------------------------------------------------
#> Male 3.603 0.034 3.536 3.669
#> Female 3.651 0.032 3.588 3.715
#> -----------------------------------------------------
#>
#> Levene's Test of Equality of Error Variances
#> F(1, 2419) = 1.306, p = 0.253
#>
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
summary(result, marginal_means = FALSE)
#> ANCOVA (One-Way ANCOVA) Results
#> -------------------------------
#>
#> - Dependent variable: life_satisfaction
#> - Factor(s): gender
#> - Covariate(s): age
#> - Sum of squares: Type III
#> - N (complete cases): 2421
#> - Missing: 79
#>
#> Tests of Between-Subjects Effects
#> ------------------------------------------------------------------------------------------------------
#> Source Type III Sum of Squares df Mean Square F Sig Partial Eta Squared
#> ------------------------------------------------------------------------------------------------------
#> Corrected Model 4.071 2 2.036 1.532 .216 0.001
#> Intercept 3410.020 1 3410.020 2565.986 <.001 0.515 ***
#> age 2.691 1 2.691 2.025 .155 0.001
#> gender 1.418 1 1.418 1.067 .302 0.000
#> Error 3213.356 2418 1.329
#> Total 35088.000 2421
#> Corrected Total 3217.428 2420
#> ------------------------------------------------------------------------------------------------------
#> R Squared = 0.001 (Adjusted R Squared = 0.000)
#>
#> Parameter Estimates
#> ---------------------------------------------------------------------------------------------------
#> Parameter B Std. Error t Sig 95% CI Lower 95% CI Upper Partial Eta Squared
#> ---------------------------------------------------------------------------------------------------
#> Intercept 3.750 0.077 48.670 <.001 3.599 3.902 0.495
#> age -0.002 0.001 -1.423 .155 -0.005 0.001 0.001
#> [gender=Male] -0.048 0.047 -1.033 .302 -0.140 0.044 0.000
#> [gender=Female] 0 (a)
#> ---------------------------------------------------------------------------------------------------
#> (a) This parameter is set to zero because it is redundant (SPSS coding: the
#> last category of each factor is the reference).
#>
#> Levene's Test of Equality of Error Variances
#> F(1, 2419) = 1.306, p = 0.253
#>
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05