tests/Test_Birnbaum_2006.R
In gary-au/pt: Computational models for prospect theory and other theories of risky decision making
library("pt")
########################
# Birnbaum, M. H. (2006). Evidence against prospect theories in gambles with positive, negative, and mixed consequences. Journal of Economic Psychology, 27(6), 737-761.
########################
########################
#
# Table 1, p.738,759
#
########################
# Stochastic dominance
# G+ = (96, 0.9; 14, 0.05; 12, 0.05)
# ~ 45.8 TAX
# G- = (96, 0.85; 90, 0.05; 12, 0.1)
# ~ 63.1 TAX
# G- > G+
choice_ids <- c(1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2, 3)
objective_consequences <- c(96, 14, 12, 96, 90, 12)
probability_strings <-
c("0.9", "0.05", "0.05", "0.85", "0.05", "0.1")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 87.7 45.77 45.77 41.93
# 2 1 2 87.3 63.1 63.1 24.2
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 87.7 42.18 70.27 17.43
# 2 1 2 87.3 41.9 69.73 17.57
########################
# Coalescing
# GS+ = (96, 0.85; 96, 0.05; 14, 0.05; 12, 0.05)
# ~ 53.1 TAX
# GS- = (96, 0.85; 90, 0.05; 12, 0.05; 12, 0.05)
# ~ 51.4 TAX
# GS+ > GS-
choice_ids <- c(1, 1, 1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 1, 2, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 4, 1, 2, 3, 4)
objective_consequences <- c(96, 96, 14, 12, 96, 90, 12, 12)
probability_strings <-
c("0.85", "0.05", "0.05", "0.05", "0.85", "0.05", "0.05", "0.05")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 87.7 53.06 53.06 34.64
# 2 1 2 87.3 51.38 51.38 35.92
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 87.7 42.18 70.27 17.43
# 2 1 2 87.3 41.9 69.73 17.57
########################
# Lower cumulative independence
# S = (44, 0.1; 40, 0.1; 2, 0.8)
# ~ 11.4 TAX
# R = (98, 0.1; 10, 0.1; 2, 0.8)
# ~ 10.9 TAX
# S > R
choice_ids <- c(1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2, 3)
objective_consequences <- c(44, 40, 2, 98, 10, 2)
probability_strings <-
c("0.1", "0.1", "0.8", "0.1", "0.1", "0.8")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 10 11.38 11.38 -1.384
# 2 1 2 12.4 10.91 10.91 1.493
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 10 8.479 11.35 -1.348
# 2 1 2 12.4 12.46 17.57 -5.171
########################
# Lower cumulative independence
# S'' = (44, 0.2; 10, 0.8)
# ~ 16.2 TAX
# R'' = (98, 0.1; 10, 0.9)
# ~ 20.4 TAX
# R'' > S''
choice_ids <- c(1, 1, 1, 1)
gamble_ids <- c(1, 1, 2, 2)
outcome_ids <- c(1, 2, 1, 2)
objective_consequences <- c(44, 10, 98, 10)
probability_strings <-
c("0.2", "0.8", "0.1", "0.9")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 16.8 16.23 16.23 0.5712
# 2 1 2 18.8 20.37 20.37 -1.573
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 16.8 12.89 18.27 -1.472
# 2 1 2 18.8 16.7 24.52 -5.723
########################
# Upper cumulative independence
# S' = (110, 0.8; 44, 0.1; 40, 0.1)
# ~ 65.0 TAX
# R' = (110, 0.8; 98, 0.1; 10, 0.1)
# ~ 69.6 TAX
# R' > S'
choice_ids <- c(1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2, 3)
objective_consequences <- c(110, 44, 40, 110, 98, 10)
probability_strings <-
c("0.8", "0.1", "0.1", "0.8", "0.1", "0.1")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 96.4 65.03 65.03 31.37
# 2 1 2 98.8 69.59 69.59 29.21
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 96.4 48.33 82.02 14.38
# 2 1 2 98.8 46.09 77.72 21.08
########################
# Upper cumulative independence
# S''' = (98, 0.8; 40, 0.2)
# ~ 68.0 TAX
# R''' = (98, 0.9; 10, 0.1)
# ~ 58.3 TAX
# S''' > R'''
choice_ids <- c(1, 1, 1, 1)
gamble_ids <- c(1, 1, 2, 2)
outcome_ids <- c(1, 2, 1, 2)
objective_consequences <- c(98, 40, 98, 10)
probability_strings <-
c("0.8", "0.2", "0.9", "0.1")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 86.4 68.04 68.04 18.36
# 2 1 2 89.2 58.29 58.29 30.91
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 86.4 44.42 74.52 11.88
# 2 1 2 89.2 42.42 70.72 18.48
gary-au/pt documentation built on May 16, 2019, 5:41 p.m.
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library("pt")
########################
# Birnbaum, M. H. (2006). Evidence against prospect theories in gambles with positive, negative, and mixed consequences. Journal of Economic Psychology, 27(6), 737-761.
########################
########################
#
# Table 1, p.738,759
#
########################
# Stochastic dominance
# G+ = (96, 0.9; 14, 0.05; 12, 0.05)
# ~ 45.8 TAX
# G- = (96, 0.85; 90, 0.05; 12, 0.1)
# ~ 63.1 TAX
# G- > G+
choice_ids <- c(1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2, 3)
objective_consequences <- c(96, 14, 12, 96, 90, 12)
probability_strings <-
c("0.9", "0.05", "0.05", "0.85", "0.05", "0.1")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 87.7 45.77 45.77 41.93
# 2 1 2 87.3 63.1 63.1 24.2
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 87.7 42.18 70.27 17.43
# 2 1 2 87.3 41.9 69.73 17.57
########################
# Coalescing
# GS+ = (96, 0.85; 96, 0.05; 14, 0.05; 12, 0.05)
# ~ 53.1 TAX
# GS- = (96, 0.85; 90, 0.05; 12, 0.05; 12, 0.05)
# ~ 51.4 TAX
# GS+ > GS-
choice_ids <- c(1, 1, 1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 1, 2, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 4, 1, 2, 3, 4)
objective_consequences <- c(96, 96, 14, 12, 96, 90, 12, 12)
probability_strings <-
c("0.85", "0.05", "0.05", "0.05", "0.85", "0.05", "0.05", "0.05")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 87.7 53.06 53.06 34.64
# 2 1 2 87.3 51.38 51.38 35.92
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 87.7 42.18 70.27 17.43
# 2 1 2 87.3 41.9 69.73 17.57
########################
# Lower cumulative independence
# S = (44, 0.1; 40, 0.1; 2, 0.8)
# ~ 11.4 TAX
# R = (98, 0.1; 10, 0.1; 2, 0.8)
# ~ 10.9 TAX
# S > R
choice_ids <- c(1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2, 3)
objective_consequences <- c(44, 40, 2, 98, 10, 2)
probability_strings <-
c("0.1", "0.1", "0.8", "0.1", "0.1", "0.8")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 10 11.38 11.38 -1.384
# 2 1 2 12.4 10.91 10.91 1.493
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 10 8.479 11.35 -1.348
# 2 1 2 12.4 12.46 17.57 -5.171
########################
# Lower cumulative independence
# S'' = (44, 0.2; 10, 0.8)
# ~ 16.2 TAX
# R'' = (98, 0.1; 10, 0.9)
# ~ 20.4 TAX
# R'' > S''
choice_ids <- c(1, 1, 1, 1)
gamble_ids <- c(1, 1, 2, 2)
outcome_ids <- c(1, 2, 1, 2)
objective_consequences <- c(44, 10, 98, 10)
probability_strings <-
c("0.2", "0.8", "0.1", "0.9")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 16.8 16.23 16.23 0.5712
# 2 1 2 18.8 20.37 20.37 -1.573
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 16.8 12.89 18.27 -1.472
# 2 1 2 18.8 16.7 24.52 -5.723
########################
# Upper cumulative independence
# S' = (110, 0.8; 44, 0.1; 40, 0.1)
# ~ 65.0 TAX
# R' = (110, 0.8; 98, 0.1; 10, 0.1)
# ~ 69.6 TAX
# R' > S'
choice_ids <- c(1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2, 3)
objective_consequences <- c(110, 44, 40, 110, 98, 10)
probability_strings <-
c("0.8", "0.1", "0.1", "0.8", "0.1", "0.1")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 96.4 65.03 65.03 31.37
# 2 1 2 98.8 69.59 69.59 29.21
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 96.4 48.33 82.02 14.38
# 2 1 2 98.8 46.09 77.72 21.08
########################
# Upper cumulative independence
# S''' = (98, 0.8; 40, 0.2)
# ~ 68.0 TAX
# R''' = (98, 0.9; 10, 0.1)
# ~ 58.3 TAX
# S''' > R'''
choice_ids <- c(1, 1, 1, 1)
gamble_ids <- c(1, 1, 2, 2)
outcome_ids <- c(1, 2, 1, 2)
objective_consequences <- c(98, 40, 98, 10)
probability_strings <-
c("0.8", "0.2", "0.9", "0.1")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 86.4 68.04 68.04 18.36
# 2 1 2 89.2 58.29 58.29 30.91
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 86.4 44.42 74.52 11.88
# 2 1 2 89.2 42.42 70.72 18.48
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