Creates a summary object that produces detailed output when printed, including group descriptives, test results with both variance assumptions, effect sizes, and confidence intervals.
Usage
# S3 method for class 't_test'
summary(
object,
descriptives = TRUE,
results = TRUE,
effect_sizes = TRUE,
digits = 3,
...
)Arguments
- object
A
t_testresult object.- descriptives
Logical. Show group descriptive statistics? (Default: TRUE)
- results
Logical. Show test results table? (Default: TRUE)
- effect_sizes
Logical. Show effect size measures? (Default: TRUE)
- digits
Number of decimal places for formatting (Default: 3).
- ...
Additional arguments (not used).
See also
t_test for the main analysis function.
Examples
result <- t_test(survey_data, life_satisfaction, group = gender)
summary(result)
#> t-Test Results
#> --------------
#>
#> - Grouping variable: gender
#> - Groups compared: Male vs. Female
#> - Confidence level: 95.0%
#> - Alternative hypothesis: two.sided
#> - Null hypothesis (mu): 0.000
#>
#>
#> --- life_satisfaction ---
#>
#> Male: mean = 3.603, n = 1149.0
#> Female: mean = 3.651, n = 1272.0
#>
#> t-test Results:
#> --------------------------------------------------------------------------------
#> Assumption t_stat df p_value mean_diff conf_int sig
#> Equal variances -1.019 2419.000 0.308 -0.048 [-0.140, 0.044]
#> Unequal variances -1.018 2384.147 0.309 -0.048 [-0.140, 0.044]
#> --------------------------------------------------------------------------------
#>
#> Effect Sizes:
#> ------------
#> Variable Cohens_d Hedges_g Glass_Delta Effect_Size
#> life_satisfaction -0.041 -0.041 -0.041 negligible
#>
#>
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
#>
#> Effect Size Interpretation:
#> - Cohen's d: pooled standard deviation (classic)
#> - Hedges' g: bias-corrected Cohen's d (preferred)
#> - Glass' Delta: control group standard deviation only
#> - Small effect: |effect| ~ 0.2
#> - Medium effect: |effect| ~ 0.5
#> - Large effect: |effect| ~ 0.8
summary(result, effect_sizes = FALSE)
#> t-Test Results
#> --------------
#>
#> - Grouping variable: gender
#> - Groups compared: Male vs. Female
#> - Confidence level: 95.0%
#> - Alternative hypothesis: two.sided
#> - Null hypothesis (mu): 0.000
#>
#>
#> --- life_satisfaction ---
#>
#> Male: mean = 3.603, n = 1149.0
#> Female: mean = 3.651, n = 1272.0
#>
#> t-test Results:
#> --------------------------------------------------------------------------------
#> Assumption t_stat df p_value mean_diff conf_int sig
#> Equal variances -1.019 2419.000 0.308 -0.048 [-0.140, 0.044]
#> Unequal variances -1.018 2384.147 0.309 -0.048 [-0.140, 0.044]
#> --------------------------------------------------------------------------------
#>
#>
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05