Advanced ANOVA analysis with comprehensive post hoc testing, effect sizes, and assumption checking. Addresses the critical issue where 68\
Usage
advancedanova(
data,
dependent,
fixed,
covariates,
wls,
model_type = "oneway",
posthoc_method = "tukey",
control_group = "",
assumptions = TRUE,
effect_sizes = TRUE,
descriptives = TRUE,
show_plots = TRUE,
plot_type = "both",
confidence_level = 0.95,
alpha_level = 0.05,
welch_correction = FALSE,
robust_anova = FALSE
)Arguments
- data
the data as a data frame
- dependent
The dependent variable from
data, variable must be numeric- fixed
The grouping variable(s) from
data, variable(s) must be a factor- covariates
Optional covariates for ANCOVA analysis
- wls
Optional weights for weighted least squares
- model_type
Type of ANOVA model to fit
- posthoc_method
Post hoc comparison method
- control_group
Control group for Dunnett's test comparisons
- assumptions
Check and report ANOVA assumptions
- effect_sizes
Calculate eta-squared, omega-squared, and Cohen's f
- descriptives
Show descriptive statistics for each group
- show_plots
Generate diagnostic and comparison plots
- plot_type
Type of plots to generate
- confidence_level
Confidence level for effect size confidence intervals
- alpha_level
Alpha level for significance testing
- welch_correction
Apply Welch correction for unequal variances
- robust_anova
Use robust ANOVA methods for non-normal data
Value
A results object containing:
results$instructions | Instructions for using the Advanced ANOVA Suite | ||||
results$descriptives | Descriptive statistics for each group | ||||
results$assumptions | Tests of ANOVA assumptions | ||||
results$anova | Main ANOVA results with effect sizes | ||||
results$tukey | Tukey Honestly Significant Difference test results | ||||
results$gameshowell | Games-Howell test for unequal variances | ||||
results$dunnett | Dunnett's test comparing treatments to control | ||||
results$bonferroni | Bonferroni-corrected pairwise comparisons | ||||
results$anovaplot | Violin plots with boxplots and group means | ||||
results$diagnosticplot | Residual plots and assumption checking | ||||
results$meansplot | Group means with confidence intervals | ||||
results$interpretation | Clinical context and interpretation guidelines |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$descriptives$asDF
as.data.frame(results$descriptives)
Examples
data('ToothGrowth')
advancedanova(data = ToothGrowth,
dependent = len,
fixed = supp)