SDy from a simplified CREPID-style activity decomposition

Computes a monetary performance index by weighting activity ratings with activity time/frequency and importance weights.

Usage

sdy_crepid(
  activities,
  ratings,
  salary,
  time_col = "time_frequency",
  importance_col = "importance",
  activity_names = NULL,
  na.rm = TRUE
)

Arguments

activities

Data frame with activity-level metadata.

ratings

Numeric matrix/data frame. Rows are employees, columns are activities.

salary

Average salary or criterion value to distribute across activities.

time_col

Name of the time/frequency column in activities.

importance_col

Name of the importance column in activities.

activity_names

Optional activity labels.

na.rm

Should missing values be removed in the SD calculation?

Value

A list with activity weights, individual criterion values, and sdy.

References

Cascio, W. F., & Ramos, R. A. (1986). Development and application of a new method for assessing job performance in behavioral/economic terms. Journal of Applied Psychology, 71, 20-28.

Examples

# Literature: Cascio and Ramos (1986).
activities <- data.frame(time_frequency = c(.4, .6), importance = c(2, 3))
ratings <- matrix(c(3, 4, 2, 5, 4, 4), ncol = 2, byrow = TRUE)
sdy_crepid(activities, ratings, salary = 80000)
#> $activity_weights
#>     activity time_frequency importance raw_weight final_weight dollar_value
#> 1 activity_1            0.4          2        0.8    0.3076923     24615.38
#> 2 activity_2            0.6          3        1.8    0.6923077     55384.62
#> 
#> $y
#> [1] 295384.6 326153.8 320000.0
#> 
#> $sdy
#> [1] 16281.55
#>