Table with alpha values — alpha

Returns a data.frame with item analyses for the provided scales.

Usage

alpha_table(
  data,
  scales,
  labels = NULL,
  round = 2,
  CI = TRUE,
  conf_level = 0.95,
  check_key = TRUE,
  keys = "auto",
  RMSEA = FALSE,
  difficulty = FALSE,
  values = NULL,
  fa = TRUE
)

Arguments

data: A data Frame
scales: A list containing vectors with variable names. Each list element defines one scale. Named list elements are used as labels.
labels: Label names for scales (defaults to named list elements in 'scales').
round: Rounds values to given decimal position.
CI: If TRUE confidence intervals are calculated.
conf_level: Confidence level (e.g. 0.95 for 95 percent).
check_key: Check_key for the psych::alpha function.
keys: Optional key argument for the psych::alpha function.
RMSEA: If TRUE RMSEA is calculated.
difficulty: If TRUE, the difficulty of the item is calculated.
values: Sets maximum and minimum valid values necessary to calculate item difficulty
fa: If TRUE, a one factor exploratory factor analyses is calculated and loadings are reported.

Value

A data frame with concise scale indices.

Examples

scales <- get_scales(ex_itrf,
  Int = scale == "ITRF" & subscale == "Int",
  Ext = scale == "ITRF" & subscale == "Ext"
)
alpha_table(ex_itrf, scales = scales, difficulty = TRUE, values = list(c(0, 3)), RMSEA = TRUE)
#> Note. values in brackets depict upper and lower bound of confidence intervals or [min,max] intervals.
#>   Scale    n n items    Alpha CI95% Std.Alph CI95% Homogeneity Discriminations
#> 1   Int 4247      19 .91 [.91, .92] .91 [.91, .92]         .36      [.49, .68]
#> 2   Ext 4616      17 .93 [.93, .93] .93 [.93, .93]         .44      [.39, .74]
#>   Difficulties        Means          SDs |Loadings| RMSEA
#> 1   [.07, .16] [0.21, 0.48] [0.51, 0.77] [.52, .70]  .154
#> 2   [.12, .32] [0.35, 0.95] [0.72, 1.04] [.38, .78]  .196