| Literature DB >> 31952550 |
Dane McCarrick1, Gayle Brewer2, Minna Lyons2, Thomas V Pollet1, Nick Neave3.
Abstract
BACKGROUND: Male height is positively associated with social dominance, and more agonistic/competitive behaviours. However, the 'Napoleon complex' or 'small man syndrome' suggests that smaller males are more assertive and punitive to compensate for lack of height and social dominance. Here, we assess possible relationships between height and punitive behaviours in a real-world setting.Entities:
Keywords: Height; Social dominance; Sport officials
Mesh:
Year: 2020 PMID: 31952550 PMCID: PMC6969448 DOI: 10.1186/s40359-020-0370-4
Source DB: PubMed Journal: BMC Psychol ISSN: 2050-7283
Means, standard deviations, and correlations with confidence intervals
| Variable | 1 | 2 | 3 | 4 | 5 | 6 | ||
|---|---|---|---|---|---|---|---|---|
| 1. Height (cm) | 176.95 | 9.81 | ||||||
| 2. Age (years) | 37.41 | 7.92 | −.10 [−.34, .16] | |||||
| 3. N Games | 26.89 | 6.19 | .04 [−.21, .29] | −.40** [−.59, −.17] | ||||
| 4. Yellows per Game | 3.16 | 0.61 | −.28* [−.49, −.03] | −.14 [−.38, .11] | .11 [−.15, .35] | |||
| 5. Reds per Game | 0.15 | 0.10 | −.34** [−.54, −.09] | −.07 [−.32, .18] | .25 [−.00, .47] | .31* [.06, .52] | ||
| 6. Fouls per Game | 22.74 | 3.26 | −.11 [−.35, .15] | −.37** [−.57, −.13] | .17 [−.08, .41] | .44** [.21, .62] | .35** [.10, .55 | |
| 7. Penalties Awarded | 4.66 | 3.16 | −.16 [−.39, .10] | −.43** [−.62, −.20] | .44** [.21, .62] | .07 [−.18, .32] | .24 [−.01, .47] | .26* [.01, .48] |
Note. M and SD are used to represent mean and standard deviation, respectively. Values in square brackets are the 95% confidence intervals for each correlation. * indicates p < .05. ** indicates p < .01
Regression models for height
| Model | Height (cm) | |
|---|---|---|
| 1 | 2 | |
| League: Championship | −.905 (3.102) | −.770 (3.093) |
| League: Premier | 1.209 (3.050) | 3.240 (3.481) |
| Age | −.225 (.188) | |
| Constant | 176.846*** (1.951) | 184.617*** (6.786) |
| Observations | 61 | 61 |
| R2 | .007 | .031 |
| Adjusted R2 | −.027 | −.020 |
| Residual Std. Error | 9.946 (df = 58) | 9.909 (df = 57) |
| F Statistic | .200 (df = 2; 58) | .611 (df = 3; 57) |
Notes
:*p < .05
**p < .01.
*** p < .001.
OLS Regression models for number of yellow cards per game
| Model | Yellows per game | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Height | −.017* (.008) | −.018* (.008) | −.016* (.007) | −.034** (.012) |
| Age | −.013 (.010) | |||
| League: Championship | .432* (.175) | −4.843 (3.077) | ||
| League: Premier | −.045 (.172) | −4.750 (3.237) | ||
| Height*League: Championship | .030 (.017) | |||
| Height*League: Premier League | .027 (.018) | |||
| Constant | 6.193*** (1.372) | 6.864*** (1.448) | 5.832*** (1.314) | 9.064*** (2.172) |
| Observations | 61 | 61 | 61 | 61 |
| R2 | .077 | .106 | .190 | .238 |
| Adjusted R2 | .061 | .075 | .147 | .169 |
| Residual Std. Error | .589 (df = 59) | .584 (df = 58) | .561 (df = 57) | .554 (df = 55) |
| F Statistic | 4.918* (df = 1; 59) | 3.426* (df = 2; 58) | 4.449** (df = 3; 57) | 3.434** (df = 5; 55) |
Notes
*p < .05.
** p < .01.
*** p < .001.
Fig. 1Number of cards per game (a: Yellow; b: Red) as a function of stature. Lines are OLS regression fits with 95% confidence intervals
Fig. 2Number of yellow cards as function of height by league. Lines are OLS regression fits per league with 95% confidence intervals
OLS Regression models for number of red cards per game
| Model | Reds per game | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| Height | −.003** (.001) | −.003* (.001) | −.003** (.001) | −.003** (.001) | −.007***(.002) |
| Yellows per Game | .036 (.020) | ||||
| Age | −.001 (.001) | ||||
| League: Championship | −.040 (.026) | −.803 (.427) | |||
| League: Premier | −.087** (.026) | −1.791*** (.449) | |||
| Height*League: Championship | .004 (.002) | ||||
| Height*League: Premier League | .010*** (.003) | ||||
| Constant | .737*** (.213) | .512* (.242) | .802*** (.227) | .742*** (.199) | 1.510*** (.302) |
| Observations | 61 | 61 | 61 | 61 | 61 |
| R2 | .114 | .163 | .125 | .259 | .413 |
| Adjusted R2 | .099 | .134 | .095 | .220 | .359 |
| Residual Std. Error | .091 (df = 59) | .089 (df = 58) | .091 (df = 58) | .085 (df = 57) | .077 (df = 55) |
| F Statistic | 7.593** (df = 1; 59) | 5.635** (df = 2; 58) | 4.139* (df = 2; 58) | 6.635*** (df = 3; 57) | 7.733*** (df = 5; 55) |
Notes
*p < .05
**p < .01
***p < .001
Fig. 3Number of red cards as function of height by league. Lines are OLS regression fits per league with 95% confidence intervals
OLS Regression models for number of penalties
| Model | Penalties awarded | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| Height | −.050 (.041) | −.064 (.037) | −.046 (.039) | −.194** (.062) | −.180** (.060) |
| Age | −.180*** (.046) | −.131* (.053) | |||
| League: Championship | −1.730 (.930) | −39.234* (15.627) | −31.899* (15.257) | ||
| League: Premier | −2.645** (.915) | −47.035** (16.437) | −37.323* (16.228) | ||
| Height*League: Championship | .212* (.088) | .171 (.086) | |||
| Height*League: Premier League | .250** (.092) | .202* (.091) | |||
| Constant | 13.540 (7.343) | 22.759** (7.019) | 14.101* (6.979) | 40.289*** (11.027) | 42.263*** (10.588) |
| Observations | 61 | 61 | 61 | 61 | 61 |
| R2 | .024 | .225 | .157 | .275 | .347 |
| Adjusted R2 | .008 | .198 | .112 | .209 | .275 |
| Residual Std. Error | 3.149 (df = 59) | 2.832 (df = 58) | 2.979 (df = 57) | 2.812 (df = 55) | 2.693 (df = 54) |
| F Statistic | 1.468 (df = 1; 59) | 8.402*** (df = 2; 58) | 3.532* (df = 3; 57) | 4.165** (df = 5; 55) | 4.788*** (df = 6; 54) |
Notes
*p < .05
**p < .01
***p < .001
Fig. 4Number of penalties as function of height by league. Lines are OLS regression fits per league with 95% confidence intervals