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Between-Case Standardized Mean Difference

Source: R/between_smd.R, R/print.sc_bcsmd.R
between_smd.Rd

Calculates a standardized mean difference from a multilevel model as described in Pustejovsky et al. (2014)

Usage

between_smd(data, ...)

# S3 method for class 'sc_bcsmd'
print(x, digits = 2, ...)

Arguments

data

Either an scdf or an object returned from the hplm() function.

...

When data is an scdf, further design parameters passed to the hplm() function.

x

An object returned by baseline_smd().

digits

The minimum number of significant digits to be use. If set to "auto" (default), values are predefined.

Functions

  • print(sc_bcsmd): Print results

References

Pustejovsky, J. E., Hedges, L. V., & Shadish, W. R. (2014). Design-Comparable Effect Sizes in Multiple Baseline Designs: A General Modeling Framework. Journal of Educational and Behavioral Statistics, 39(5), 368–393. https://doi.org/10.3102/1076998614547577

Examples

des <- design(
  n = 150,
  phase_design = list(A = 10, B = 10, A2 = 10, B2 = 10, c = 10),
  level = list(B = 1, A2 = 0, B2 = 1, c = 1),
  random_start_value = TRUE
)
study <- random_scdf(des)
between_smd(study)
#> Between-Case Standardized Mean Difference
#> 
#>   Effect BC-SMD Only random intercept
#>   phaseB   0.88                  0.98
#>  phaseA2   0.86                  0.95
#>  phaseB2   1.76                  1.95
#>   phasec   2.59                  2.87

model <- hplm(study, slope = FALSE, contrast_level = "preceding")
between_smd(model)
#> Between-Case Standardized Mean Difference
#> 
#>   Effect BC-SMD Only random intercept
#>   phaseB   0.88                  0.97
#>  phaseA2   0.01                  0.01
#>  phaseB2   0.89                  0.99
#>   phasec   0.88                  0.98