Background

In a 2 (taboo vs. standard) cell design, participants read about one of five taboo transactions, or one of five standard economic transactions, depending on condition. They were then asked, in a random order, about the actors’ benefit from the transaction and the power balance in the transaction.

Attention check

What are the roles of Person A and Person B in the transaction that took place?
The correct answer is: Person A paid money and Person B received money

cond failcheck passcheck
nontaboo 18 184
taboo 10 190

Alright, that leaves us with 374, pretty evenly distributed between conditions.

Demographics

Race

race N Perc
asian 29 7.75
black 50 13.37
hispanic 13 3.48
multiracial 30 8.02
white 247 66.04
NA 5 1.34

Gender

gender N Perc
man 196 52.41
woman 170 45.45
NA 8 2.14

Age

age_mean age_sd
37.77807 10.47691

Education

edu N Perc
noHS 1 0.27
GED 94 25.13
2yearColl 43 11.50
4yearColl 166 44.39
MA 49 13.10
PHD 16 4.28
NA 5 1.34

Income

Analysis

Condition -> Benefit

Descriptives

cond benefit_A_m benefit_A_sd benefit_B_m benefit_B_sd
nontaboo 1.277174 1.273659 1.2880435 1.417559
taboo 1.657895 1.366189 0.1894737 1.807069

Two-way Repeated Measures ANOVA

Effect DFn DFd F p p<.05 ges
cond 1 372 12.949 0.000363
0.015
person 1 372 39.184 0.000000
0.057
cond:person 1 372 40.362 0.000000
0.059

Bonferroni-corrected post-hoc comparisons: Party

person Effect DFn DFd F p p<.05 ges p.adj
benefit_A cond 1 372 7.759 0.006
0.020 0.012
benefit_B cond 1 372 42.609 0.000
0.103 0.000

Bonferroni-corrected post-hoc comparisons: Condition

cond Effect DFn DFd F p p<.05 ges p.adj
nontaboo person 1 183 0.006 0.936 1.64e-05 1
taboo person 1 189 61.390 0.000
1.74e-01 0

One-sample t-tests

Buyers in Taboo Condition: t(189) = 16.73, p < .001, d = 1.21

Buyers in Standard Condition: t(183) = 12.33, p < .001, d = 0.91

Sellers in Taboo Condition: t(189) = 1.45, p = .925, d = 0.10

Sellers in Standard Condition: t(183) = 12.33, p < .001, d = 0.91

Condition -> Power

Let’s take a look at the effect on power. Power was rated from -3 (Buyer has much more power) to 3 (Seller has much more power).

Descriptives

cond power_M power_SD
nontaboo 0.30 1.66
taboo 0.12 1.95

Oh nooo! The seller has more power? Could this be because the buyer might seem desperate in some of these (there’s only one kidney for them, only one doctor’s appointment, etc.)?

One-sample t-tests

Taboo Condition:

t(189) = 0.86, p = .392, d = 0.06
Non-Taboo Condition:

t(183) = 2.48, p = .014, d = 0.18

The sellers in the nontaboo condition have more power than buyers. No difference in power for the taboo condition. Wow.

Plot: Condition -> Power


Mediation model: condition -> power -> seller benefit

0 = Standard; 1 = Taboo

Call: psych::mediate(y = benefit_B ~ condition + (power), data = formed)

Direct effect estimates (traditional regression) (c’) X + M on Y benefit_B se t df Prob Intercept 1.25 0.12 10.43 371 1.72e-22 condition -1.07 0.17 -6.44 371 3.77e-10 power 0.14 0.05 3.01 371 2.78e-03

R = 0.35 R2 = 0.12 F = 26.3 on 2 and 371 DF p-value: 2.08e-11

Total effect estimates (c) (X on Y) benefit_B se t df Prob Intercept 1.29 0.12 10.74 372 1.31e-23 condition -1.10 0.17 -6.53 372 2.19e-10

‘a’ effect estimates (X on M) power se t df Prob Intercept 0.30 0.13 2.28 372 0.0234 condition -0.18 0.19 -0.98 372 0.3290

‘b’ effect estimates (M on Y controlling for X) benefit_B se t df Prob power 0.14 0.05 3.01 371 0.00278

‘ab’ effect estimates (through all mediators) benefit_B boot sd lower upper condition -0.03 -0.03 0.03 -0.09 0.02

a = -0.18 (p = 0.329); b = 0.14 (p = 0.003); direct = -1.1 (p = 0); indirect = -1.07 (p = 0).

Order effects: Benefit first

Condition -> Benefit

Descriptives

cond benefit_A_m benefit_A_sd benefit_B_m benefit_B_sd
nontaboo 1.209302 1.372985 1.2209302 1.529330
taboo 1.519608 1.474069 0.2352941 1.780958

Two-way Repeated Measures ANOVA

Effect DFn DFd F p p<.05 ges
cond 1 186 5.821 0.017000
0.012
person 1 186 12.576 0.000494
0.040
cond:person 1 186 13.040 0.000392
0.042

Bonferroni-corrected post-hoc comparisons: Party

person Effect DFn DFd F p p<.05 ges p.adj
benefit_A cond 1 186 2.201 1.40e-01 0.012 0.2800000
benefit_B cond 1 186 16.240 8.13e-05
0.080 0.0001626

Bonferroni-corrected post-hoc comparisons: Condition

cond Effect DFn DFd F p p<.05 ges p.adj
nontaboo person 1 85 0.003 9.59e-01 1.62e-05 1.00e+00
taboo person 1 101 22.755 6.20e-06
1.35e-01 1.24e-05

One-sample t-tests

Buyers in Taboo Condition: t(101) = 10.41, p < .001, d = 1.03

Buyers in Standard Condition: t(85) = 7.40, p < .001, d = 0.80

Sellers in Taboo Condition: t(101) = 1.33, p = .907, d = 0.13

Sellers in Standard Condition: t(85) = 7.40, p < .001, d = 0.80

Condition -> Power

Let’s take a look at the effect on power. Power was rated from -3 (Buyer has much more power) to 3 (Seller has much more power).

Descriptives

cond power_M power_SD
nontaboo 0.37 1.59
taboo 0.22 1.80

One-sample t-tests

Taboo Condition:

t(101) = 1.21, p = .229, d = 0.12
Non-Taboo Condition:

t(85) = 2.16, p = .033, d = 0.23

Plot: Condition -> Power


Order effects: Power first

Condition -> Benefit

Descriptives

cond benefit_A_m benefit_A_sd benefit_B_m benefit_B_sd
nontaboo 1.336735 1.183598 1.3469388 1.316838
taboo 1.818182 1.218115 0.1363636 1.845665

Two-way Repeated Measures ANOVA

Effect DFn DFd F p p<.05 ges
cond 1 184 6.488 1.2e-02
0.017
person 1 184 31.364 1.0e-07
0.082
cond:person 1 184 32.134 1.0e-07
0.083

Bonferroni-corrected post-hoc comparisons: Party

person Effect DFn DFd F p p<.05 ges p.adj
benefit_A cond 1 184 7.463 7e-03
0.039 1.4e-02
benefit_B cond 1 184 26.912 6e-07
0.128 1.1e-06

Bonferroni-corrected post-hoc comparisons: Condition

cond Effect DFn DFd F p p<.05 ges p.adj
nontaboo person 1 97 0.004 0.95 1.68e-05 1
taboo person 1 87 42.705 0.00
2.26e-01 0

One-sample t-tests

Buyers in Taboo Condition: t(87) = 14.00, p < .001, d = 1.49

Buyers in Standard Condition: t(97) = 10.13, p < .001, d = 1.02

Sellers in Taboo Condition: t(87) = 0.69, p = .755, d = 0.07

Sellers in Standard Condition: t(97) = 10.13, p < .001, d = 1.02

Condition -> Power

Let’s take a look at the effect on power. Power was rated from -3 (Buyer has much more power) to 3 (Seller has much more power).

Descriptives

cond power_M power_SD
nontaboo 0.24 1.73
taboo 0.01 2.11

One-sample t-tests

Taboo Condition:

t(87) = 0.05, p = .960, d < 0.01
Non-Taboo Condition:

t(97) = 1.40, p = .164, d = 0.14

Plot: Condition -> Power


By Scenario

Power by scenario

Scenario 1: Cancerous cell-phone tower vs. noisy street
Scenario 2: Kidney vs. car
Scenario 3: Hazardous chemicals vs. furniture
Scenario 4: Beauty product side effects vs. bugs and glitches
Scenario 5: Doctor’s appointment vs. concert tickets

transaction cond n power_M power_SD
1 nontaboo 37 0.00 1.58
1 taboo 39 0.05 1.82
2 nontaboo 32 0.72 1.46
2 taboo 42 1.48 1.85
3 nontaboo 38 0.68 1.14
3 taboo 37 0.35 1.65
4 nontaboo 38 -1.08 1.75
4 taboo 38 -1.18 1.57
5 nontaboo 39 1.23 1.35
5 taboo 34 -0.26 1.83

Seller benefit by scenario

Scenario 1: Cancerous cell-phone tower vs. noisy street
Scenario 2: Kidney vs. car
Scenario 3: Hazardous chemicals vs. furniture
Scenario 4: Beauty product side effects vs. bugs and glitches
Scenario 5: Doctor’s appointment vs. concert tickets

transaction cond n benefit_B_M benefit_B_SD
1 nontaboo 37 -0.62 1.42
1 taboo 39 -1.28 1.69
2 nontaboo 32 2.28 0.77
2 taboo 42 1.29 1.29
3 nontaboo 38 1.89 0.80
3 taboo 37 0.27 1.73
4 nontaboo 38 1.58 0.98
4 taboo 38 0.47 1.64
5 nontaboo 39 1.41 0.94
5 taboo 34 0.12 1.70