Z_identities: Z Identities

In samplr: Compare Human Performance to Sampling Algorithms

Z Identities

Description

Calculates identities Z1 to Z18 as defined in \insertCitecostello2016PeopleConditionalProbability,zhu2020BayesianSamplerGenericsamplr. Probability theory predicts that these will all equal 0.

Usage

Z_identities(
  a = NULL,
  b = NULL,
  a_and_b = NULL,
  a_or_b = NULL,
  a_given_b = NULL,
  b_given_a = NULL,
  a_given_not_b = NULL,
  b_given_not_a = NULL,
  a_and_not_b = NULL,
  b_and_not_a = NULL,
  not_a = NULL,
  not_b = NULL
)

Arguments

a, b, a_and_b, a_or_b, a_given_b, b_given_a, a_given_not_b, b_given_not_a, a_and_not_b, b_and_not_a	Probability estimates given by participants
not_a, not_b	Probability estimates given by participants. If not given, they'll default to 1-a and 1-b respectively

Details

If some of the probability estimates are not given, calculation will proceed and equalities that cannot be calculated will be coded as NA.

Value

Dataframe with identities Z1 to Z18

References

\insertAllCited

Examples

Z_identities(
 a=.5, 
 b=.1, 
 a_and_b=.05, 
 a_or_b=.55, 
 a_given_b=.5,
 b_given_a=.1,
 a_given_not_b=.5,
 b_given_not_a=.1,
 a_and_not_b=.45,
 b_and_not_a=.05,
 )
#Get identities for a set of participants
library(magrittr)
library(dplyr)
library(tidyr)
data.frame(
 ID = LETTERS[1:20],
 a=runif(20),
 b=runif(20),
 a_and_b=runif(20),
 a_or_b=runif(20),
 a_given_b=runif(20),
 b_given_a=runif(20),
 a_given_not_b=runif(20),
 b_given_not_a=runif(20),
 a_and_not_b=runif(20),
 b_and_not_a=runif(20),
 not_a=runif(20),
 not_b=runif(20)
) %>% 
 group_by(ID) %>% 
 do(
   Z_identities(
     .$a,
     .$b,
     .$a_and_b,
     .$a_or_b,
     .$a_given_b,
     .$b_given_a,
     .$a_given_not_b,
     .$b_given_not_a,
     .$a_and_not_b,
     .$b_and_not_a,
     .$not_a,
     .$not_b
   )
 )

samplr documentation built on April 4, 2025, 12:30 a.m.