ez_anova: Analysis of variance
In psyntur: Helper Tools for Teaching Statistical Data Analysis

Description Usage Arguments Value Examples

This is wrapper to the ez::ezANOVA() function.

ez_anova(
  data,
  dv,
  wid,
  within = NULL,
  within_full = NULL,
  within_covariates = NULL,
  between = NULL,
  between_covariates = NULL,
  observed = NULL,
  diff = NULL,
  reverse_diff = FALSE,
  type = 2,
  white.adjust = FALSE,
  detailed = FALSE,
  return_aov = FALSE
)

`data`	Data frame containing the data to be analyzed.
`dv`	Name of the column in `data` that contains the dependent variable. Values in this column must be numeric.
`wid`	Name of the column in `data` that contains the variable specifying the case/Ss identifier. This should be a unique value per case/Ss.
`within`	Names of columns in `data` that contain predictor variables that are manipulated (or observed) within-Ss.
`within_full`	Same as within, but intended to specify the full within-Ss design in cases where the data have not already been collapsed to means per condition specified by `within` and when `within` only specifies a subset of the full design.
`within_covariates`	Names of columns in `data` that contain predictor variables that are manipulated (or observed) within-Ss and are to serve as covariates in the analysis.
`between`	Names of columns in `data` that contain predictor variables that are manipulated (or observed) between-Ss.
`between_covariates`	Names of columns in `data` that contain predictor variables that are manipulated (or observed) between-Ss and are to serve as covariates in the analysis.
`observed`	Names of columns in `data` that are already specified in either `within` or `between` that contain predictor variables that are observed variables (i.e. not manipulated).
`diff`	Names of any variables to collapse to a difference score. If a single value, may be specified by name alone; if multiple values, must be specified as a .() list.
`reverse_diff`	Logical. If TRUE, triggers reversal of the difference collapse requested by `diff`. Take care with variables with more than 2 levels.
`type`	Numeric value (either `1`, `2` or `3`) specifying the Sums of Squares type to employ when data are unbalanced (eg. when group sizes differ).
`white.adjust`	Only affects behaviour if the design contains only between-Ss predictor variables. If not FALSE, the value is passed as the white.adjust argument to Anova, which provides heteroscedasticity correction.
`detailed`	Logical. If TRUE, returns extra information (sums of squares columns, intercept row, etc.) in the ANOVA table.
`return_aov`	Logical. If TRUE, computes and returns an aov object corresponding to the requested ANOVA (useful for computing post-hoc contrasts).

A list containing one or more components as returned by ez::ezANOVA().

ez_anova(data = selfesteem2_long,
            dv = score,
            wid = id,
            within = c(time, treatment),
            detailed = TRUE,
            return_aov = TRUE)