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Disruptive or stabilising selection on one trait

Source: R/analyze_disruptive_selection.R
analyze_disruptive_selection.Rd

Estimates the linear (beta) and quadratic (gamma) selection gradients of a single trait. Gamma is positive under disruptive selection and negative under stabilising selection.

Usage

analyze_disruptive_selection(
  data,
  fitness_col,
  trait_col,
  fitness_type = c("auto", "binary", "count", "continuous"),
  standardize = TRUE,
  group = NULL,
  return_grouped = FALSE
)

Arguments

data

A data frame containing fitness and trait measurements.

fitness_col

A string specifying the name of the fitness column.

trait_col

A string specifying the name of the single trait column.

fitness_type

A string indicating the fitness type: "auto" (detect from the data), "binary", or "continuous". Default is "auto".

standardize

Logical indicating whether to standardize the trait to mean 0 and SD 1. Default is TRUE.

group

Optional string specifying a grouping variable; standardisation and relative fitness are then computed within each group.

return_grouped

Logical; if TRUE and group is given, the gradients are estimated separately for each group and returned with a Group column. Default is FALSE.

Value

A data frame with one row per gradient (Term, Type, Beta_Coefficient, Standard_Error, P_Value, Variance).

Examples

analyze_disruptive_selection(bumpus, "survival", "total_length")
#>            Term      Type Beta_Coefficient Standard_Error     P_Value
#> 1  total_length    Linear       -0.2364547     0.07915422 0.004487591
#> 2 total_length² Quadratic       -0.3245696     0.13732470 0.019694542
#>      Variance
#> 1 0.006265391
#> 2 0.018858072
analyze_disruptive_selection(bumpus, "survival", "total_length",
                             group = "sex", return_grouped = TRUE)
#>                   Term      Type Beta_Coefficient Standard_Error      P_Value
#> male.1    total_length    Linear       -0.3694482     0.08243345 0.0002002952
#> male.2   total_length² Quadratic       -0.1042183     0.13610059 0.7263041851
#> female.1  total_length    Linear       -0.1672317     0.16841847 0.3189315357
#> female.2 total_length² Quadratic       -0.3448404     0.36946919 0.3292407999
#>             Variance  Group
#> male.1   0.006795274   male
#> male.2   0.018523371   male
#> female.1 0.028364780 female
#> female.2 0.136507482 female