TOSTER (version 0.8.3)

dataTOSTtwo: TOST Independent Samples T-Test

Description

TOST Independent Samples T-Test for jamovi. This function is not meant to be utilized in R. See t_TOST function.

Usage

dataTOSTtwo(
  data,
  deps,
  group,
  var_equal = FALSE,
  hypothesis = "EQU",
  low_eqbound = -0.5,
  high_eqbound = 0.5,
  eqbound_type = "raw",
  alpha = 0.05,
  desc = FALSE,
  plots = FALSE,
  descplots = FALSE,
  low_eqbound_d = -999999999,
  high_eqbound_d = -999999999,
  smd_type = "g"
)

Value

A results object containing:

results$text					a html
results$tost					a table
results$eqb					a table
results$effsize					a table
results$desc					a table
results$plots					an array of images
results$descplots					an array of images

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$tost$asDF

as.data.frame(results$tost)

Arguments

data

the data as a data frame

deps

a vector of strings naming dependent variables in data

group

a string naming the grouping variable in data; must have two levels

var_equal

TRUE or FALSE (default), assume equal variances

hypothesis

'EQU' for equivalence (default), or 'MET' for minimal effects test, the alternative hypothesis.

low_eqbound

a number (default: -0.5) the lower equivalence/MET bounds

high_eqbound

a number (default: 0.5) the upper equivalence/MET bounds

eqbound_type

'SMD' (default) or 'raw'; whether the bounds are specified in Cohen's d or raw units respectively

alpha

alpha level (default = 0.05)

desc

TRUE or FALSE (default), provide descriptive statistics

plots

TRUE or FALSE (default), provide effect size plots

descplots

TRUE or FALSE (default), provide plots

low_eqbound_d

deprecated

high_eqbound_d

deprecated

smd_type

'd' (default) or 'g'; whether the calculated effect size is biased (d) or bias-corrected (g).

References

Berger, R. L., & Hsu, J. C. (1996). Bioequivalence Trials, Intersection-Union Tests and Equivalence Confidence Sets. Statistical Science, 11(4), 283-302.

Gruman, J. A., Cribbie, R. A., & Arpin-Cribbie, C. A. (2007). The effects of heteroscedasticity on tests of equivalence. Journal of Modern Applied Statistical Methods, 6(1), 133-140, formula for Welch's t-test on page 135

Examples

library(TOSTER)

## Load iris dataset, remove one of the three groups so two are left

data<-iris[which(iris$Species!="versicolor"),]

## TOST procedure on the raw data

dataTOSTtwo(data, deps="Sepal.Width", group="Species", var_equal = TRUE, low_eqbound = -0.5,
            high_eqbound = 0.5, alpha = 0.05, desc = TRUE, plots = TRUE)