samplr (version 1.1.0)

Z_identities: Z Identities

Description

Calculates identities Z1 to Z18 as defined in costello2016PeopleConditionalProbability,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
)

Value

Dataframe with identities Z1 to Z18

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.

References

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
   )
 )