statsExpressions (version 0.6.2)

expr_t_robust: Expression containing results from a robust t-test

Description

Expression containing results from a robust t-test

Usage

expr_t_robust(
  data,
  x,
  y,
  subject.id = NULL,
  paired = FALSE,
  k = 2L,
  conf.level = 0.95,
  tr = 0.1,
  nboot = 100,
  output = "expression",
  ...
)

Arguments

data

A dataframe (or a tibble) from which variables specified are to be taken. A matrix or tables will not be accepted.

x

The grouping variable from the dataframe data.

y

The response (a.k.a. outcome or dependent) variable from the dataframe data.

subject.id

In case of repeated measures design (paired = TRUE, i.e.), this argument specifies the subject or repeated measures id. Note that if this argument is NULL (which is the default), the function assumes that the data has already been sorted by such an id by the user and creates an internal identifier. So if your data is not sorted and you leave this argument unspecified, the results can be inaccurate.

paired

Logical that decides whether the experimental design is repeated measures/within-subjects or between-subjects. The default is FALSE.

k

Number of digits after decimal point (should be an integer) (Default: k = 2L).

conf.level

Scalar between 0 and 1. If unspecified, the defaults return 95% confidence/credible intervals (0.95).

tr

Trim level for the mean when carrying out robust tests. If you get error stating "Standard error cannot be computed because of Winsorized variance of 0 (e.g., due to ties). Try to decrease the trimming level.", try to play around with the value of tr, which is by default set to 0.1. Lowering the value might help.

nboot

Number of bootstrap samples for computing confidence interval for the effect size (Default: 100).

output

If "expression", will return expression with statistical details, while "dataframe" will return a dataframe containing the results.

...

Additional arguments (currently ignored).

References

For more details, see- https://indrajeetpatil.github.io/statsExpressions/articles/stats_details.html

Examples

# NOT RUN {
# for reproducibility
set.seed(123)
library(statsExpressions)

# between-subjects design -----------------------------------------------

# with defaults
expr_t_robust(
  data = sleep,
  x = group,
  y = extra
)

# within-subjects design -----------------------------------------------
expr_t_robust(
  data = dplyr::filter(bugs_long, condition %in% c("LDLF", "LDHF")),
  x = condition,
  y = desire,
  paired = TRUE,
  subject.id = subject
)
# }