1
Appendix A: Moderating effect of winning/losing contest
2
3
Using forward stepwise regression, three separate moderator regression analyses
4
were performed with one of the behavioral indices as the dependent variable. The sex of
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the stimulus person was dummy-coded as 0 for a man and 1 for a woman and the
6
outcome of the competition was dummy-coded as 0 for the losers and 1 for the winners.
7
For calculating the change in T during the competition we used the unstandardized
8
residuals from regressing T1 on T2. In Step 1, the main effects of Sex of the stimulus
9
person, the Outcome of the competition and the Change in T during the competition were
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entered. In Step 2, the Sex × Change in T interaction and the Outcome × Change-in-T
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interaction and the Sex × Outcome interaction were added. In step 3 the three way
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interaction term Sex × Change in T interaction × Outcome was added.
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14
Interest in the stimulus person
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The model in step 1, including Sex of the stimulus person, Outcome of the
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competition and the Change in T during the competition as predictor variables, did not
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explain a significant amount of variance in the index of interest in the stimulus person
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(F3,73 = 0.37, p = 0.778). However, entering the three two-way interaction terms in step 2
20
significantly increased the amount of variance explained (ΔF3,70 = 3.76, p = 0.015,
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adjusted R² = 7.9%, ΔR² = 13.7%). In this step, the only significant effect was the 2-way
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interaction between the change in T and sex (β = 0.336, p = 0.030). See the main
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manuscript for significance tests of the slopes. In step 3, entering the interaction term Sex
1
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× Change in T interaction × Outcome did not explain a significant amount of variance in
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the index of interest in the stimulus person (ΔF1,69 = 0.46, p = 0.500).
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Self-presentation
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The model in step 1, including Sex of the stimulus person, Outcome of the
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competition and the Change in T during the competition as predictor variables, did not
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explain a significant amount of variance in the index of self-presentation (F3,73 = 0.16, p
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= 0.925). However, entering the three two-way interaction terms in step 2 significantly
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increased the amount of variance explained (ΔF3,70 = 2.86, p = 0.043, adjusted R² = 3.9%,
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ΔR² = 10.9%). In this step, the only significant effect was the 2-way interaction between
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the change in T and sex (β = 0.329, p = 0.037). See the main manuscript for significance
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tests of the slopes. In step 3, entering the interaction term Sex × Change in T interaction ×
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Outcome did not explain a significant amount of variance in the index of self-presentation
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(ΔF1,69 = 0.35, p = 0.558).
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2
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Positive facial cues
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The model in step 1, including Sex of the stimulus person, Outcome of the
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competition and the Change in T during the competition as predictor variables, explained
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a significant amount of variance in positive facial cues (ΔF3,73 = 2.87, p = 0.042, adjusted
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R² = 6.9%, ΔR² = 10.5%). In this step, the only significant effect was the main effect of T
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change (β = 0.276, p = 0.017). Additionally, entering the three two-way interaction terms
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in step 2 did not increase the amount of variance explained (ΔF3,70 = 2.00, p = 0.122). In
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step 3, entering the interaction term Sex × Change in T interaction × Outcome did not
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explain a significant amount of variance in the index of positive facial cues (ΔF1,69 =
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0.12, p = 0.736).
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3
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Appendix B: Effects of baseline T
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Using forward stepwise regression, three separate moderator regression
55
analyses were performed with one of the behavioral indices as the dependent variable.
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The sex of the stimulus person was dummy-coded as 0 for a man and 1 for a woman and
57
the outcome of the competition was dummy-coded as 0 for the losers and 1 for the
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winners. In Step 1, the main effects of Sex of the stimulus person, the Outcome of the
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competition and Baseline T were entered. In Step 2, the Sex × Baseline T interaction, the
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Outcome × Baseline T interaction, and the Sex × Outcome interaction were added. In step
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3 the three way interaction term Sex × Baseline T × Outcome interaction was added.
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Interest in the stimulus person
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The model in step 1, including Sex of the stimulus person, Outcome of the
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competition and Baseline T as predictor variables, did not explain a significant amount of
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variance in the of interest in the stimulus person (F3,73 = 0.85, p = 0.968). Entering the
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three two-way interaction terms in step 2 did not significantly increase the amount of
69
variance explained (ΔF3,70 = 0.47, p = 0.707). In step 3, entering the interaction term Sex
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× Baseline T × Outcome did not explain a significant amount of variance in the index of
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interest in the stimulus person (ΔF1,69 = 0.70, p = 0.407).
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Self presentation
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The model in step 1, including Sex of the stimulus person, Outcome of the
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competition and Baseline T as predictor variables, did not explain a significant amount of
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variance in the index self presentation (F3,73 = 0.21, p = 0.886). Entering the three two-
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way interaction terms in step 2 did not significantly increase the amount of variance
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explained (ΔF3,70 = 0.04, p = 0.988). In step 3, entering the interaction term Sex ×
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Baseline T × Outcome did not explain a significant amount of variance in the index self
81
presentation (ΔF1,69 = 0.34, p = 0.565).
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Positive facial cues
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The model in step 1, including Sex of the stimulus person, Outcome of the
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competition and Baseline T as predictor variables, did not explain a significant amount of
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variance in the index positive facial cues (F3,73 = 0.90, p = 0.446). Entering the three two-
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way interaction terms in step 2 did not significantly increase the amount of variance
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explained (ΔF3,70 = 0.43, p = 0.730). In step 3, entering the interaction term Sex ×
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Baseline T × Outcome did not explain a significant amount of variance in the index self
91
presentation (ΔF1,69 = 1.71, p = 0.195).
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Appendix C: Controlling for the opponent’s psychological state (see ref. [20])
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Using forward stepwise regression, three separate moderator regression analyses
96
were performed with one of the behavioural indices as the dependent variable. The sex of
97
the stimulus person was dummy-coded as 0 for a man and 1 for a woman. For calculating
98
the change in T during the competition we used the unstandardized residuals from
99
regressing T1 on T2. In Step 1, the main effects of Sex of the stimulus person, and the
100
Change in T during the competition were entered. Additionally, as a control we added in
101
Step 1 the opponents’ self-reported self-efficacy, perceived importance of the
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competition, and expectancy to win or lose. In Step 2, the Sex × Change in T interaction
103
was added.
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Interest in the stimulus person
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The model in step 1 included the following predictor variables: (i) Sex of the
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stimulus person, (ii) Change in T during the competition, (iii) Opponents’ self-reported
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self-efficacy, (iv) Opponents’ perceived importance of the competition, and (v)
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Opponents’ expectancy to win or lose. This model did not explain a significant amount of
111
variance in the index of interest in the stimulus person (F5,71 = 1.88, p = 0.109). However,
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entering the interaction terms in step 2 marginally increased the amount of variance
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explained (ΔF1,70 = 3.85, p = 0.054, adjusted R² = 9.1%, ΔR² = 4.6%). See the main
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manuscript for significance tests of the slopes.
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Self-presentation
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The model in step 1 included the following predictor variables: (i) Sex of the
119
stimulus person, (ii) Change in T during the competition, (iii) Opponents’ self-reported
120
self-efficacy, (iv) Opponents’ perceived importance of the competition, and (v)
121
Opponents’ expectancy to win or lose. This model did not explain a significant amount of
122
variance in the index of self-presentation (F5,71 = 0.80, p = 0.553). However, entering the
123
interaction terms in step 2 significantly increased the amount of variance explained
124
(ΔF1,70 = 5.29, p = 0.024, adjusted R² = 4.4%, ΔR² = 6.7%). %). See the main manuscript
125
for significance tests of the slopes.
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Positive facial cues
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The model in step 1 included the following predictor variables: (i) Sex of the
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stimulus person, (ii) Change in T during the competition, (iii) Opponents’ self-reported
131
self-efficacy, (iv) Opponents’ perceived importance of the competition, and (v)
132
Opponents’ expectancy to win or lose. This model explained a significant amount of the
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variance in positive facial cues (ΔF5,71 = 4.16, p = 0.002, adjusted R² = 17.2%, R² =
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22.7%). Entering the interaction term in step 2 did not increase the amount of variance
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explained (ΔF1,70 = 2.05, p = 0.156).
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Appendix D: Regression analysis with only one factor (overall affiliative behaviour)
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We averaged the scores from all nine items to create one composite factor, which
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we term overall affiliative behaviour. The factor loadings for this variable were as
140
follows:
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Table 1. Factor loading of the behavioral items on only one factor
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Nº
Behavioral item
Loading
1
-Gave attention to stimulus person
0.954
2
-Showed interest in stimulus person
0.971
3
-Interacted confidently with stimulus person
0.945
4
-Asked questions
0.866
5
-Was talkative
0.925
6
-Talked about himself
0.864
7
-Revealed details about himself
0.817
8
-Was smiling
0.650
9
-Made eye contact
0.865
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The model in step 1, including sex of the stimulus person and the change in T
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during the competition as predictor variables, did not explain a significant amount of
147
variance in overall affiliative behaviour (F2,74 = 0.77, p = 0.469). However, entering the
8
148
interaction term in step 2 significantly increased the amount of variance explained (ΔF1,73
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= 5.68, p = 0.020, adjusted R² = 5.4%, ΔR² = 7.1%). In this step, there were no main
150
effects of sex of the stimulus person (p = 0.737) or change in T (p = 0.525), but there was
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a significant 2-way interaction between the change in T and sex (β = 0.356, p = 0.020).
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Significance tests of the slopes revealed that while the change in T did not affect overall
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affiliative behaviour when interacting with a man (t73 = -0.639, β = -0.096, p = 0.525), a
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greater change in T was associated with a higher score for overall affiliative behaviour
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when interacting with a woman (t73 = 2.62, β = 0.443, p = 0.011).
9