Preliminary Results
2022-10-17
Manipulation checks For Competence vs. Relatedness Conditions
(Does Erdat feel like he has satisfactory relationships?)
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 2.7 2.7 3.408 0.0663 .
Relatedness 1 335.1 335.1 419.409 <2e-16 ***
Competence:Relatedness 1 0.0 0.0 0.048 0.8271
Residuals 200 159.8 0.8
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = man1 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 0.23 -0.016 0.48 0.07
$Relatedness
diff lwr upr p adj
High-Low 2.6 2.3 2.8 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 0.37 -0.11 0.85 0.18
Low:High-Low:Low 2.60 2.13 3.08 0.00
High:High-Low:Low 2.92 2.45 3.40 0.00
Low:High-High:Low 2.23 1.78 2.68 0.00
High:High-High:Low 2.55 2.10 2.99 0.00
High:High-Low:High 0.32 -0.12 0.76 0.24
Table 1
Means and standard deviations for man1 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 1.45 0.74 4.06 1.00
High 1.83 0.94 4.38 0.84
Note. M and SD represent mean and standard deviation, respectively. 
(Does Erdat satisfy his need to have a warm, genuine, and meaningful relationship with his colleagues?)
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 3.1 3.1 4.233 0.0409 *
Relatedness 1 462.7 462.7 640.040 <2e-16 ***
Competence:Relatedness 1 2.7 2.7 3.698 0.0559 .
Residuals 200 144.6 0.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = man6 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -0.25 -0.48 -0.01 0.04
$Relatedness
diff lwr upr p adj
High-Low 3 2.8 3.3 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 0.14 -0.32 0.594 0.86
Low:High-Low:Low 3.27 2.82 3.723 0.00
High:High-Low:Low 2.95 2.50 3.396 0.00
Low:High-High:Low 3.13 2.70 3.560 0.00
High:High-High:Low 2.81 2.38 3.233 0.00
High:High-Low:High -0.32 -0.74 0.097 0.19
Table 2
Means and standard deviations for man6 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 1.29 0.71 4.56 0.72
High 1.42 0.82 4.23 1.06
Note. M and SD represent mean and standard deviation, respectively. 
Competence check 1
(Is Erdat pleased with his performance at work?)
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 389.5 389.5 722.271 <2e-16 ***
Relatedness 1 1.8 1.8 3.399 0.0667 .
Competence:Relatedness 1 0.2 0.2 0.333 0.5648
Residuals 200 107.9 0.5
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = man2 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 2.8 2.6 3 0
$Relatedness
diff lwr upr p adj
High-Low 0.19 -0.013 0.39 0.07
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 2.84 2.45 3.24 0.00
Low:High-Low:Low 0.25 -0.14 0.65 0.34
High:High-Low:Low 2.98 2.59 3.36 0.00
Low:High-High:Low -2.59 -2.96 -2.22 0.00
High:High-High:Low 0.13 -0.23 0.50 0.78
High:High-Low:High 2.72 2.36 3.09 0.00
Table 3
Means and standard deviations for man2 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 1.52 0.63 1.78 0.69
High 4.37 0.79 4.50 0.79
Note. M and SD represent mean and standard deviation, respectively. 
Competence check 2
(Is Erdat pleased with his performance at work?)
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 414.0 414.0 615.059 < 2e-16 ***
Relatedness 1 5.2 5.2 7.794 0.00575 **
Competence:Relatedness 1 0.0 0.0 0.000 0.99544
Residuals 200 134.6 0.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = man5 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 2.9 2.6 3.1 0
$Relatedness
diff lwr upr p adj
High-Low 0.32 0.094 0.55 0.01
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 2.87 2.428 3.31 0.00
Low:High-Low:Low 0.32 -0.115 0.76 0.23
High:High-Low:Low 3.19 2.757 3.62 0.00
Low:High-High:Low -2.55 -2.959 -2.13 0.00
High:High-High:Low 0.32 -0.088 0.73 0.18
High:High-Low:High 2.87 2.462 3.27 0.00
Table 4
Means and standard deviations for man5 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 1.38 0.54 1.70 0.94
High 4.25 0.93 4.57 0.76
Note. M and SD represent mean and standard deviation, respectively. 
Manipulation checks For Competence vs. Autonomous Conditions
Autonomy Check1
###(Does Erdat feel in control of his thoughts, emotions and behaviors?)
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 262.64 262.64 381.98 < 2e-16 ***
Autonomy 1 37.47 37.47 54.49 5.48e-12 ***
Competence:Autonomy 1 7.04 7.04 10.23 0.00163 **
Residuals 181 124.45 0.69
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = man2 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 2.4 2.1 2.6 0
$Autonomy
diff lwr upr p adj
High-Low 0.9 0.66 1.1 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 1.98 1.534 2.43 0.00
Low:High-Low:Low 0.52 0.073 0.96 0.02
High:High-Low:Low 3.28 2.834 3.72 0.00
Low:High-High:Low -1.46 -1.915 -1.01 0.00
High:High-High:Low 1.30 0.846 1.75 0.00
High:High-Low:High 2.76 2.313 3.21 0.00
Table 5
Means and standard deviations for man4 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 1.87 0.92 3.00 1.17
High 2.27 1.21 4.18 1.09
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 2 rows containing non-finite values (stat_summary).
Removed 2 rows containing non-finite values (stat_summary).
Competence check 1
(Is Erdat pleased with his performance at work?)
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 262.64 262.64 381.98 < 2e-16 ***
Autonomy 1 37.47 37.47 54.49 5.48e-12 ***
Competence:Autonomy 1 7.04 7.04 10.23 0.00163 **
Residuals 181 124.45 0.69
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = man2 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 2.4 2.1 2.6 0
$Autonomy
diff lwr upr p adj
High-Low 0.9 0.66 1.1 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 1.98 1.534 2.43 0.00
Low:High-Low:Low 0.52 0.073 0.96 0.02
High:High-Low:Low 3.28 2.834 3.72 0.00
Low:High-High:Low -1.46 -1.915 -1.01 0.00
High:High-High:Low 1.30 0.846 1.75 0.00
High:High-Low:High 2.76 2.313 3.21 0.00
Table 6
Means and standard deviations for man2 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 1.38 0.49 1.89 0.90
High 3.36 1.19 4.65 0.57
Note. M and SD represent mean and standard deviation, respectively. 
Competence check 2
(Is Erdat pleased with his performance at work?)
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 201.86 201.86 224.10 < 2e-16 ***
Autonomy 1 40.57 40.57 45.04 2.4e-10 ***
Competence:Autonomy 1 10.08 10.08 11.19 0.001 **
Residuals 181 163.04 0.90
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = man5 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 2.1 1.8 2.4 0
$Autonomy
diff lwr upr p adj
High-Low 0.94 0.66 1.2 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 1.61 1.10 2.12 0.00
Low:High-Low:Low 0.48 -0.03 0.99 0.07
High:High-Low:Low 3.02 2.51 3.53 0.00
Low:High-High:Low -1.13 -1.65 -0.62 0.00
High:High-High:Low 1.41 0.90 1.93 0.00
High:High-Low:High 2.54 2.03 3.06 0.00
Table 7
Means and standard deviations for man5 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 1.48 0.68 1.96 0.73
High 3.09 1.47 4.50 0.69
Note. M and SD represent mean and standard deviation, respectively. 
Q1: Pleased with his Job
Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 167.82 167.82 244.785 < 2e-16 ***
Relatedness 1 22.01 22.01 32.100 5.05e-08 ***
Competence:Relatedness 1 3.94 3.94 5.746 0.0174 *
Residuals 200 137.11 0.69
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n1 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 1.8 1.6 2 0
$Relatedness
diff lwr upr p adj
High-Low 0.66 0.43 0.89 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 2.15 1.704 2.59 0.00
Low:High-Low:Low 0.96 0.516 1.40 0.00
High:High-Low:Low 2.55 2.110 2.99 0.00
Low:High-High:Low -1.19 -1.608 -0.77 0.00
High:High-High:Low 0.40 -0.015 0.81 0.06
High:High-Low:High 1.59 1.181 2.00 0.00
Table 8
Means and standard deviations for n1 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 1.52 0.80 2.48 0.95
High 3.67 0.81 4.07 0.74
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 25.40 25.40 41.337 1.13e-09 ***
Autonomy 1 255.80 255.80 416.366 < 2e-16 ***
Competence:Autonomy 1 1.61 1.61 2.626 0.107
Residuals 179 109.97 0.61
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
206 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n1 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.75 0.52 0.97 0
$Autonomy
diff lwr upr p adj
High-Low 2.4 2.1 2.6 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.55 0.12 0.97 0.01
Low:High-Low:Low 2.18 1.76 2.60 0.00
High:High-Low:Low 3.10 2.68 3.53 0.00
Low:High-High:Low 1.63 1.21 2.06 0.00
High:High-High:Low 2.56 2.13 2.98 0.00
High:High-Low:High 0.92 0.50 1.35 0.00
Table 9
Means and standard deviations for n1 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 1.28 0.71 3.46 0.96
High 1.82 0.78 4.38 0.65
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 2 rows containing non-finite values (stat_summary).
Removed 2 rows containing non-finite values (stat_summary).
Pleased with his life
Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 42.71 42.71 79.246 3.34e-16 ***
Relatedness 1 70.37 70.37 130.588 < 2e-16 ***
Competence:Relatedness 1 2.09 2.09 3.886 0.0501 .
Residuals 200 107.78 0.54
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n2 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 0.92 0.71 1.1 0
$Relatedness
diff lwr upr p adj
High-Low 1.2 0.97 1.4 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 1.19 0.79 1.58 0.00
Low:High-Low:Low 1.40 1.01 1.79 0.00
High:High-Low:Low 2.18 1.79 2.57 0.00
Low:High-High:Low 0.21 -0.16 0.58 0.47
High:High-High:Low 0.99 0.62 1.36 0.00
High:High-Low:High 0.78 0.42 1.14 0.00
Table 10
Means and standard deviations for n2 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 1.71 0.77 3.11 0.77
High 2.90 0.69 3.89 0.71
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 21.14 21.14 25.363 1.15e-06 ***
Autonomy 1 54.92 54.92 65.898 7.24e-14 ***
Competence:Autonomy 1 2.55 2.55 3.059 0.082 .
Residuals 180 150.01 0.83
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
205 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n2 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.68 0.41 0.94 0
$Autonomy
diff lwr upr p adj
High-Low 1.1 0.83 1.4 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.43 -0.058 0.92 0.10
Low:High-Low:Low 0.86 0.374 1.35 0.00
High:High-Low:Low 1.77 1.275 2.26 0.00
Low:High-High:Low 0.43 -0.067 0.93 0.12
High:High-High:Low 1.33 0.834 1.83 0.00
High:High-Low:High 0.90 0.408 1.40 0.00
Table 11
Means and standard deviations for n2 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 1.83 0.78 2.70 0.87
High 2.27 0.84 3.60 1.14
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Burnout
Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 53.57 53.57 55.414 2.84e-12 ***
Relatedness 1 26.50 26.50 27.414 4.14e-07 ***
Competence:Relatedness 1 2.33 2.33 2.406 0.122
Residuals 200 193.33 0.97
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = burnout ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -1 -1.3 -0.75 0
$Relatedness
diff lwr upr p adj
High-Low -0.72 -0.99 -0.45 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -0.83 -1.35 -0.297 0.00
Low:High-Low:Low -0.49 -1.02 0.029 0.07
High:High-Low:Low -1.75 -2.27 -1.230 0.00
Low:High-High:Low 0.33 -0.16 0.826 0.31
High:High-High:Low -0.92 -1.41 -0.434 0.00
High:High-Low:High -1.26 -1.74 -0.769 0.00
Table 12
Means and standard deviations for burnout as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 4.14 0.78 3.65 1.05
High 3.32 0.87 2.39 1.14
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 26.68 26.68 27.93 3.58e-07 ***
Autonomy 1 34.56 34.56 36.19 9.70e-09 ***
Competence:Autonomy 1 10.19 10.19 10.67 0.0013 **
Residuals 181 172.86 0.96
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = burnout ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low -0.76 -1 -0.48 0
$Autonomy
diff lwr upr p adj
High-Low -0.86 -1.1 -0.58 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low -0.28 -0.80 0.25 0.52
Low:High-Low:Low -0.40 -0.93 0.12 0.19
High:High-Low:Low -1.62 -2.14 -1.10 0.00
Low:High-High:Low -0.12 -0.66 0.41 0.93
High:High-High:Low -1.34 -1.87 -0.81 0.00
High:High-Low:High -1.22 -1.75 -0.69 0.00
Table 13
Means and standard deviations for burnout as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 3.99 0.94 3.59 0.82
High 3.71 1.07 2.37 1.06
Note. M and SD represent mean and standard deviation, respectively. 
Feels Anxious Regarding his work life
Comptence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 161 161 141.6 <2e-16 ***
Relatedness 1 11 11 10.0 0.002 **
Competence:Relatedness 1 6 6 5.5 0.020 *
Residuals 197 223 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
188 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n4 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -1.8 -2.1 -1.5 0
$Relatedness
diff lwr upr p adj
High-Low -0.48 -0.77 -0.18 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -1.42 -2.00 -0.84 0.00
Low:High-Low:Low -0.10 -0.67 0.46 0.97
High:High-Low:Low -2.24 -2.80 -1.67 0.00
Low:High-High:Low 1.32 0.78 1.86 0.00
High:High-High:Low -0.81 -1.35 -0.28 0.00
High:High-Low:High -2.13 -2.66 -1.60 0.00
Table 14
Means and standard deviations for n4 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 4.38 0.62 4.28 0.94
High 2.96 1.23 2.15 1.27
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 3 rows containing non-finite values (stat_summary).
Removed 3 rows containing non-finite values (stat_summary).
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 93 93 73 6e-15 ***
Autonomy 1 18 18 14 2e-04 ***
Competence:Autonomy 1 28 28 22 5e-06 ***
Residuals 181 232 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n4 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low -1.4 -1.7 -1.1 0
$Autonomy
diff lwr upr p adj
High-Low -0.63 -0.96 -0.3 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low -0.63 -1.24 -0.024 0.04
Low:High-Low:Low 0.14 -0.47 0.743 0.94
High:High-Low:Low -2.06 -2.66 -1.452 0.00
Low:High-High:Low 0.77 0.16 1.387 0.01
High:High-High:Low -1.42 -2.04 -0.809 0.00
High:High-Low:High -2.20 -2.81 -1.583 0.00
Table 15
Means and standard deviations for n4 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 4.17 1.15 4.30 0.87
High 3.53 1.27 2.11 1.20
Note. M and SD represent mean and standard deviation, respectively. 
Feel annoyed regarding his current working conditions
Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 136 136 139.0 <2e-16 ***
Relatedness 1 62 62 63.2 1e-13 ***
Competence:Relatedness 1 9 9 9.6 0.002 **
Residuals 200 195 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n6 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -1.6 -1.9 -1.4 0
$Relatedness
diff lwr upr p adj
High-Low -1.1 -1.4 -0.83 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -1.21 -1.744 -0.68 0.00
Low:High-Low:Low -0.64 -1.169 -0.12 0.01
High:High-Low:Low -2.72 -3.242 -2.20 0.00
Low:High-High:Low 0.57 0.073 1.07 0.02
High:High-High:Low -1.51 -2.000 -1.01 0.00
High:High-Low:High -2.08 -2.565 -1.59 0.00
Table 16
Means and standard deviations for n6 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 4.31 0.75 3.67 1.12
High 3.10 1.14 1.59 0.85
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 65 65 71 1e-14 ***
Autonomy 1 124 124 135 <2e-16 ***
Competence:Autonomy 1 11 11 12 6e-04 ***
Residuals 180 166 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
205 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n6 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low -1.2 -1.5 -0.91 0
$Autonomy
diff lwr upr p adj
High-Low -1.6 -1.9 -1.4 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low -0.66 -1.2 -0.146 0.01
Low:High-Low:Low -1.15 -1.7 -0.635 0.00
High:High-Low:Low -2.81 -3.3 -2.295 0.00
Low:High-High:Low -0.49 -1.0 0.036 0.08
High:High-High:Low -2.15 -2.7 -1.625 0.00
High:High-Low:High -1.66 -2.2 -1.136 0.00
Table 16
Means and standard deviations for n6 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 4.40 0.96 3.24 0.91
High 3.73 1.07 1.59 0.88
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Q7: Likely to experience conflict with his colleagues in the future (burnout3)
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 0 0 0.2 0.6
Relatedness 1 65 65 69.6 1e-14 ***
Competence:Relatedness 1 14 14 14.7 2e-04 ***
Residuals 200 186 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = burnout3 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 0.062 -0.2 0.33 0.64
$Relatedness
diff lwr upr p adj
High-Low -1.1 -1.4 -0.86 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 0.58 0.059 1.097 0.02
Low:High-Low:Low -0.58 -1.091 -0.062 0.02
High:High-Low:Low -1.04 -1.552 -0.531 0.00
Low:High-High:Low -1.15 -1.640 -0.669 0.00
High:High-High:Low -1.62 -2.101 -1.138 0.00
High:High-Low:High -0.46 -0.942 0.012 0.06
Table 16
Means and standard deviations for burnout3 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 3.60 0.86 3.02 1.04
High 4.17 0.71 2.55 1.16
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 0 0.1 0.1 0.82
Autonomy 1 7 7.4 6.3 0.01 *
Competence:Autonomy 1 4 3.6 3.1 0.08 .
Residuals 181 213 1.2
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = burnout3 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.036 -0.28 0.35 0.82
$Autonomy
diff lwr upr p adj
High-Low -0.4 -0.71 -0.084 0.01
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.32 -0.26 0.906 0.48
Low:High-Low:Low -0.12 -0.70 0.457 0.95
High:High-Low:Low -0.36 -0.94 0.218 0.37
Low:High-High:Low -0.45 -1.04 0.144 0.21
High:High-High:Low -0.68 -1.27 -0.095 0.02
High:High-Low:High -0.24 -0.83 0.347 0.72
Table 17
Means and standard deviations for burnout3 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 3.17 0.97 3.04 1.19
High 3.49 1.10 2.80 1.07
Note. M and SD represent mean and standard deviation, respectively. 
Feels Helpless
Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 105 105 93 <2e-16 ***
Relatedness 1 59 59 53 9e-12 ***
Competence:Relatedness 1 14 14 13 4e-04 ***
Residuals 199 225 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
186 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n8 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -1.4 -1.7 -1.1 0
$Relatedness
diff lwr upr p adj
High-Low -1.1 -1.4 -0.79 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -0.91 -1.49 -0.34 0.00
Low:High-Low:Low -0.51 -1.08 0.06 0.10
High:High-Low:Low -2.50 -3.06 -1.93 0.00
Low:High-High:Low 0.40 -0.14 0.93 0.22
High:High-High:Low -1.59 -2.12 -1.06 0.00
High:High-Low:High -1.99 -2.51 -1.46 0.00
Table 18
Means and standard deviations for n8 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 4.12 1.03 3.61 1.02
High 3.21 1.18 1.62 1.02
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 45 45 49 6e-11 ***
Autonomy 1 80 80 86 <2e-16 ***
Competence:Autonomy 1 38 38 41 1e-09 ***
Residuals 180 167 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
205 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n8 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low -0.99 -1.3 -0.71 0
$Autonomy
diff lwr upr p adj
High-Low -1.3 -1.6 -1 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low -0.062 -0.58 0.46 0.99
Low:High-Low:Low -0.418 -0.94 0.10 0.16
High:High-Low:Low -2.302 -2.82 -1.79 0.00
Low:High-High:Low -0.356 -0.88 0.17 0.30
High:High-High:Low -2.239 -2.76 -1.71 0.00
High:High-Low:High -1.884 -2.41 -1.36 0.00
Table 19
Means and standard deviations for n8 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 4.06 1.00 3.64 1.00
High 4.00 0.85 1.76 0.99
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Q9: Feels ashamed about his current working conditions
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 236 236 233.5 <2e-16 ***
Relatedness 1 1 1 0.8 0.369
Competence:Relatedness 1 9 9 9.0 0.003 **
Residuals 198 200 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
187 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n9 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -2.2 -2.4 -1.9 0
$Relatedness
diff lwr upr p adj
High-Low -0.13 -0.41 0.15 0.37
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -1.71 -2.25 -1.163 0.00
Low:High-Low:Low 0.33 -0.21 0.869 0.39
High:High-Low:Low -2.23 -2.77 -1.697 0.00
Low:High-High:Low 2.04 1.53 2.543 0.00
High:High-High:Low -0.53 -1.03 -0.023 0.04
High:High-Low:High -2.56 -3.06 -2.065 0.00
Table 20
Means and standard deviations for n9 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 3.71 1.08 4.04 0.95
High 2.00 1.19 1.47 0.79
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 2 rows containing non-finite values (stat_summary).
Removed 2 rows containing non-finite values (stat_summary).
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 159 159 137.6 <2e-16 ***
Autonomy 1 1 1 0.8 0.4
Competence:Autonomy 1 13 13 11.6 8e-04 ***
Residuals 180 208 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
205 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n9 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low -1.9 -2.2 -1.5 0
$Autonomy
diff lwr upr p adj
High-Low -0.14 -0.45 0.17 0.39
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low -1.33 -1.90 -0.75 0.00
Low:High-Low:Low 0.39 -0.19 0.96 0.30
High:High-Low:Low -2.01 -2.59 -1.44 0.00
Low:High-High:Low 1.71 1.13 2.30 0.00
High:High-High:Low -0.69 -1.28 -0.10 0.01
High:High-Low:High -2.40 -2.99 -1.82 0.00
Table 21
Means and standard deviations for n9 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 3.46 1.35 3.85 1.01
High 2.13 1.08 1.44 0.76
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Q10: Likely to remain optimistic regarding his future?
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 87 87 105.9 <2e-16 ***
Relatedness 1 20 20 24.6 2e-06 ***
Competence:Relatedness 1 1 1 1.5 0.2
Residuals 200 164 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n10 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 1.3 1.1 1.6 0
$Relatedness
diff lwr upr p adj
High-Low 0.63 0.38 0.88 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 1.17 0.680 1.65 0.00
Low:High-Low:Low 0.47 -0.016 0.95 0.06
High:High-Low:Low 1.94 1.462 2.42 0.00
Low:High-High:Low -0.70 -1.155 -0.24 0.00
High:High-High:Low 0.77 0.323 1.23 0.00
High:High-Low:High 1.47 1.028 1.92 0.00
Table 20
Means and standard deviations for n10 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 1.74 0.80 2.20 0.88
High 2.90 1.03 3.68 0.88
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 31 31 39 3e-09 ***
Autonomy 1 53 53 67 4e-14 ***
Competence:Autonomy 1 16 16 20 1e-05 ***
Residuals 181 143 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n10 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.82 0.56 1.1 0
$Autonomy
diff lwr upr p adj
High-Low 1.1 0.82 1.3 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.22 -0.26 0.70 0.64
Low:High-Low:Low 0.50 0.02 0.97 0.04
High:High-Low:Low 1.89 1.41 2.36 0.00
Low:High-High:Low 0.28 -0.20 0.76 0.44
High:High-High:Low 1.67 1.19 2.15 0.00
High:High-Low:High 1.39 0.91 1.87 0.00
Table 21
Means and standard deviations for n10 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 1.92 0.82 2.41 1.02
High 2.13 0.76 3.80 0.93
Note. M and SD represent mean and standard deviation, respectively. 
Q11: Likely to show effort to make progress in his work?
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 52 52 58 9e-13 ***
Relatedness 1 11 11 13 5e-04 ***
Competence:Relatedness 1 15 15 16 8e-05 ***
Residuals 200 179 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n11 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 1 0.75 1.3 0
$Relatedness
diff lwr upr p adj
High-Low 0.47 0.21 0.74 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 1.618 1.109 2.127 0.00
Low:High-Low:Low 1.048 0.543 1.552 0.00
High:High-Low:Low 1.589 1.089 2.090 0.00
Low:High-High:Low -0.571 -1.047 -0.094 0.01
High:High-High:Low -0.029 -0.501 0.443 1.00
High:High-Low:High 0.542 0.074 1.009 0.02
Table 22
Means and standard deviations for n11 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 2.29 0.94 3.33 0.97
High 3.90 0.91 3.88 0.95
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 8 8 7.5 0.007 **
Autonomy 1 65 65 61.1 4e-13 ***
Competence:Autonomy 1 0 0 0.2 0.628
Residuals 180 192 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
205 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n11 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.42 0.12 0.72 0.01
$Autonomy
diff lwr upr p adj
High-Low 1.2 0.89 1.5 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.32 -0.238 0.87 0.45
Low:High-Low:Low 1.12 0.562 1.67 0.00
High:High-Low:Low 1.58 1.031 2.14 0.00
Low:High-High:Low 0.80 0.235 1.36 0.00
High:High-High:Low 1.27 0.704 1.83 0.00
High:High-Low:High 0.47 -0.096 1.03 0.14
Table 23
Means and standard deviations for n11 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 2.44 0.94 3.56 1.14
High 2.76 1.17 4.02 0.86
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Q12: Likely to look for another job
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 60 60 44.5 2e-10 ***
Relatedness 1 17 17 12.3 6e-04 ***
Competence:Relatedness 1 7 7 5.3 0.02 *
Residuals 200 269 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n12 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -1.1 -1.4 -0.76 0
$Relatedness
diff lwr upr p adj
High-Low -0.57 -0.89 -0.25 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -0.70 -1.326 -0.08 0.02
Low:High-Low:Low -0.17 -0.790 0.45 0.89
High:High-Low:Low -1.62 -2.238 -1.01 0.00
Low:High-High:Low 0.53 -0.052 1.11 0.09
High:High-High:Low -0.92 -1.500 -0.34 0.00
High:High-Low:High -1.45 -2.026 -0.88 0.00
Table 24
Means and standard deviations for n12 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 3.36 1.27 3.19 1.10
High 2.65 1.23 1.73 1.05
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 2 2 1.2 0.3
Autonomy 1 108 108 80.4 4e-16 ***
Competence:Autonomy 1 17 17 12.3 6e-04 ***
Residuals 181 243 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n12 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.18 -0.15 0.52 0.28
$Autonomy
diff lwr upr p adj
High-Low -1.5 -1.9 -1.2 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.80 0.18 1.43 0.01
Low:High-Low:Low -0.94 -1.56 -0.32 0.00
High:High-Low:Low -1.33 -1.95 -0.71 0.00
Low:High-High:Low -1.74 -2.37 -1.11 0.00
High:High-High:Low -2.13 -2.76 -1.50 0.00
High:High-Low:High -0.39 -1.02 0.24 0.37
Table 25
Means and standard deviations for n12 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 3.40 1.14 2.46 1.19
High 4.20 1.06 2.07 1.24
Note. M and SD represent mean and standard deviation, respectively. 
Q13: Likely to move to another company that offers a 20% raise in his salary
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 11 10.7 6.2 0.01 *
Relatedness 1 26 25.5 14.7 2e-04 ***
Competence:Relatedness 1 2 2.4 1.4 0.24
Residuals 200 346 1.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n13 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -0.46 -0.82 -0.094 0.01
$Relatedness
diff lwr upr p adj
High-Low -0.71 -1.1 -0.34 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -0.25 -0.96 0.46 0.79
Low:High-Low:Low -0.48 -1.18 0.23 0.30
High:High-Low:Low -1.17 -1.86 -0.47 0.00
Low:High-High:Low -0.22 -0.89 0.44 0.82
High:High-High:Low -0.91 -1.57 -0.26 0.00
High:High-Low:High -0.69 -1.34 -0.04 0.03
Table 26
Means and standard deviations for n13 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 3.81 1.27 3.33 1.29
High 3.56 1.50 2.64 1.18
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 5 5 2.9 0.09 .
Autonomy 1 41 41 24.2 2e-06 ***
Competence:Autonomy 1 3 3 2.0 0.16
Residuals 181 307 2
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = n13 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.32 -0.054 0.7 0.09
$Autonomy
diff lwr upr p adj
High-Low -0.94 -1.3 -0.56 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.072 -0.628 0.773 0.99
Low:High-Low:Low -1.207 -1.903 -0.510 0.00
High:High-Low:Low -0.598 -1.295 0.099 0.12
Low:High-High:Low -1.279 -1.987 -0.571 0.00
High:High-High:Low -0.670 -1.378 0.038 0.07
High:High-Low:High 0.609 -0.095 1.313 0.12
Table 27
Means and standard deviations for n13 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 3.75 1.30 2.54 1.24
High 3.82 1.17 3.15 1.48
Note. M and SD represent mean and standard deviation, respectively. 
Q14: In two years, Erdat’s relationship with his colleagues will be (1 = worse, 5 = better)
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 3 2.8 2.4 0.12
Relatedness 1 2 2.4 2.0 0.16
Competence:Relatedness 1 3 3.3 2.8 0.09 .
Residuals 200 233 1.2
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s14 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 0.23 -0.063 0.53 0.12
$Relatedness
diff lwr upr p adj
High-Low 0.22 -0.083 0.51 0.16
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -0.032 -0.612 0.55 1.00
Low:High-Low:Low -0.056 -0.631 0.52 0.99
High:High-Low:Low 0.423 -0.148 0.99 0.22
Low:High-High:Low -0.024 -0.567 0.52 1.00
High:High-High:Low 0.455 -0.084 0.99 0.13
High:High-Low:High 0.478 -0.055 1.01 0.10
Table 28
Means and standard deviations for s14 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 2.67 1.05 2.61 1.11
High 2.63 1.17 3.09 0.98
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 1 0.8 0.6 0.424
Autonomy 1 12 11.9 10.1 0.002 **
Competence:Autonomy 1 1 1.0 0.8 0.360
Residuals 181 212 1.2
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s14 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low -0.13 -0.44 0.19 0.42
$Autonomy
diff lwr upr p adj
High-Low 0.51 0.19 0.82 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.0097 -0.573 0.59 1.00
Low:High-Low:Low 0.6513 0.072 1.23 0.02
High:High-Low:Low 0.3687 -0.211 0.95 0.35
Low:High-High:Low 0.6415 0.053 1.23 0.03
High:High-High:Low 0.3589 -0.230 0.95 0.39
High:High-Low:High -0.2826 -0.868 0.30 0.60
Table 29
Means and standard deviations for s14 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 2.48 0.99 3.13 1.05
High 2.49 1.08 2.85 1.21
Note. M and SD represent mean and standard deviation, respectively. 
Q15: In two years, Erdat’s performance will be (1 = worse, 5 = better)
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 10 9.8 6.1 0.01 *
Relatedness 1 3 2.5 1.6 0.21
Competence:Relatedness 1 0 0.0 0.0 0.89
Residuals 199 318 1.6
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
186 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s15 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 0.44 0.09 0.79 0.01
$Relatedness
diff lwr upr p adj
High-Low 0.22 -0.13 0.58 0.21
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 0.42 -0.2549 1.10 0.37
Low:High-Low:Low 0.20 -0.4758 0.87 0.87
High:High-Low:Low 0.67 0.0017 1.34 0.05
Low:High-High:Low -0.23 -0.8632 0.41 0.79
High:High-High:Low 0.25 -0.3856 0.88 0.74
High:High-Low:High 0.47 -0.1530 1.10 0.21
Table 30
Means and standard deviations for s15 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 2.69 1.16 2.89 1.31
High 3.12 1.35 3.36 1.21
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 0 0 0.0 1.0
Autonomy 1 55 55 37.1 7e-09 ***
Competence:Autonomy 1 2 2 1.4 0.2
Residuals 180 268 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
205 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s15 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.0073 -0.35 0.36 0.97
$Autonomy
diff lwr upr p adj
High-Low 1.1 0.74 1.5 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low -0.21 -0.87 0.44 0.84
Low:High-Low:Low 0.89 0.24 1.54 0.00
High:High-Low:Low 1.10 0.44 1.76 0.00
Low:High-High:Low 1.10 0.44 1.77 0.00
High:High-High:Low 1.31 0.64 1.98 0.00
High:High-Low:High 0.21 -0.46 0.87 0.85
Table 31
Means and standard deviations for s15 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 2.48 1.27 3.37 1.24
High 2.27 1.05 3.58 1.31
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Q16: Likelihood for Erdat to show commitment towards his job?
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 55 55 51.7 1e-11 ***
Relatedness 1 3 3 3.1 0.08 .
Competence:Relatedness 1 6 6 5.2 0.02 *
Residuals 199 210 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
186 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s16 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 1 0.75 1.3 0
$Relatedness
diff lwr upr p adj
High-Low 0.25 -0.032 0.54 0.08
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 0.69 0.133 1.25 0.01
Low:High-Low:Low -0.10 -0.654 0.45 0.96
High:High-Low:Low 1.25 0.704 1.80 0.00
Low:High-High:Low -0.79 -1.309 -0.27 0.00
High:High-High:Low 0.56 0.049 1.07 0.03
High:High-Low:High 1.35 0.846 1.86 0.00
Table 32
Means and standard deviations for s16 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 2.20 1.12 2.09 0.98
High 2.88 0.96 3.45 1.06
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 9 9 8.5 0.004 **
Autonomy 1 39 39 35.7 1e-08 ***
Competence:Autonomy 1 2 2 1.8 0.185
Residuals 180 195 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
205 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s16 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.45 0.15 0.75 0
$Autonomy
diff lwr upr p adj
High-Low 0.92 0.61 1.2 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.23 -0.334 0.79 0.72
Low:High-Low:Low 0.72 0.155 1.28 0.01
High:High-Low:Low 1.35 0.794 1.91 0.00
Low:High-High:Low 0.49 -0.080 1.06 0.12
High:High-High:Low 1.12 0.558 1.69 0.00
High:High-Low:High 0.64 0.069 1.20 0.02
Table 33
Means and standard deviations for s16 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 2.06 0.98 2.78 1.08
High 2.29 1.01 3.41 1.09
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Q17: Likelihood to quit his job?
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 39 39 29.1 2e-07 ***
Relatedness 1 9 9 7.0 0.009 **
Competence:Relatedness 1 8 8 5.8 0.017 *
Residuals 199 265 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
186 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s17 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low -0.88 -1.2 -0.56 0
$Relatedness
diff lwr upr p adj
High-Low -0.43 -0.75 -0.11 0.01
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low -0.470 -1.09 0.15 0.21
Low:High-Low:Low -0.011 -0.63 0.61 1.00
High:High-Low:Low -1.264 -1.88 -0.65 0.00
Low:High-High:Low 0.459 -0.12 1.04 0.17
High:High-High:Low -0.794 -1.37 -0.22 0.00
High:High-Low:High -1.253 -1.82 -0.68 0.00
Table 34
Means and standard deviations for s17 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 3.59 1.30 3.57 1.19
High 3.12 0.98 2.32 1.15
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 2 2 1.5 0.222
Autonomy 1 39 39 30.1 1e-07 ***
Competence:Autonomy 1 10 10 7.4 0.007 **
Residuals 181 237 1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s17 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low -0.21 -0.54 0.13 0.22
$Autonomy
diff lwr upr p adj
High-Low -0.92 -1.3 -0.59 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.27 -0.35 0.881 0.68
Low:High-Low:Low -0.47 -1.08 0.140 0.19
High:High-Low:Low -1.12 -1.74 -0.512 0.00
Low:High-High:Low -0.74 -1.36 -0.115 0.01
High:High-High:Low -1.39 -2.01 -0.768 0.00
High:High-Low:High -0.65 -1.27 -0.034 0.03
Table 35
Means and standard deviations for s17 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 3.65 1.18 3.17 1.10
High 3.91 1.00 2.52 1.28
Note. M and SD represent mean and standard deviation, respectively. 
Q18: Likelihood for positive aspects to compensate the negative one
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 22 22.4 29.1 2e-07 ***
Relatedness 1 1 1.4 1.8 0.2
Competence:Relatedness 1 0 0.0 0.0 0.8
Residuals 200 153 0.8
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
185 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s18 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 0.66 0.42 0.91 0
$Relatedness
diff lwr upr p adj
High-Low 0.17 -0.076 0.41 0.18
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 0.64 0.17 1.114 0.00
Low:High-Low:Low 0.14 -0.33 0.607 0.86
High:High-Low:Low 0.83 0.37 1.296 0.00
Low:High-High:Low -0.50 -0.94 -0.063 0.02
High:High-High:Low 0.19 -0.25 0.627 0.68
High:High-Low:High 0.69 0.26 1.126 0.00
Table 36
Means and standard deviations for s18 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 2.45 1.02 2.59 0.74
High 3.10 0.89 3.29 0.87
Note. M and SD represent mean and standard deviation, respectively. 
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 3 3.2 4.2 0.04 *
Autonomy 1 16 16.0 20.8 9e-06 ***
Competence:Autonomy 1 0 0.0 0.0 0.96
Residuals 181 139 0.8
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
204 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s18 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 0.26 0.0098 0.52 0.04
$Autonomy
diff lwr upr p adj
High-Low 0.59 0.33 0.84 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 0.25 -0.22 0.72 0.52
Low:High-Low:Low 0.58 0.11 1.05 0.01
High:High-Low:Low 0.84 0.37 1.31 0.00
Low:High-High:Low 0.33 -0.14 0.81 0.27
High:High-High:Low 0.59 0.12 1.07 0.01
High:High-Low:High 0.26 -0.21 0.73 0.48
Table 37
Means and standard deviations for s18 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 2.40 0.84 2.98 0.91
High 2.64 0.86 3.24 0.90
Note. M and SD represent mean and standard deviation, respectively. 
Q19: Would you like to be in Erdat’s place?
### Competence vs. Relatedness
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 564 564 140 <2e-16 ***
Relatedness 1 283 283 70 9e-15 ***
Competence:Relatedness 1 50 50 12 5e-04 ***
Residuals 199 801 4
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
186 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s19 ~ Competence + Relatedness + Competence * Relatedness, data = df1)
$Competence
diff lwr upr p adj
High-Low 3.3 2.8 3.9 0
$Relatedness
diff lwr upr p adj
High-Low 2.4 1.8 2.9 0
$`Competence:Relatedness`
diff lwr upr p adj
High:Low-Low:Low 2.4 1.30 3.457 0.00
Low:High-Low:Low 1.3 0.25 2.384 0.01
High:High-Low:Low 5.7 4.62 6.750 0.00
Low:High-High:Low -1.1 -2.07 -0.053 0.03
High:High-High:Low 3.3 2.30 4.312 0.00
High:High-Low:High 4.4 3.37 5.366 0.00
Table 38
Means and standard deviations for s19 as a function of a 2(Competence) X 2(Relatedness) design
Relatedness
Low High
Competence M SD M SD
Low 1.33 0.79 2.65 1.88
High 3.71 2.30 7.02 2.42
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).
Competence vs. Autonomy
Df Sum Sq Mean Sq F value Pr(>F)
Competence 1 211 211 49 5e-11 ***
Autonomy 1 370 370 86 <2e-16 ***
Competence:Autonomy 1 51 51 12 7e-04 ***
Residuals 180 774 4
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
205 observations deleted due to missingness Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = s19 ~ Competence + Autonomy + Competence * Autonomy, data = df2)
$Competence
diff lwr upr p adj
High-Low 2.1 1.5 2.7 0
$Autonomy
diff lwr upr p adj
High-Low 2.8 2.2 3.4 0
$`Competence:Autonomy`
diff lwr upr p adj
High:Low-Low:Low 1.04 -0.077 2.2 0.08
Low:High-Low:Low 1.79 0.678 2.9 0.00
High:High-Low:Low 4.94 3.829 6.0 0.00
Low:High-High:Low 0.76 -0.378 1.9 0.31
High:High-High:Low 3.90 2.772 5.0 0.00
High:High-Low:High 3.14 2.016 4.3 0.00
Table 39
Means and standard deviations for s19 as a function of a 2(Competence) X 2(Autonomy) design
Autonomy
Low High
Competence M SD M SD
Low 1.58 1.37 3.38 2.07
High 2.62 1.87 6.52 2.76
Note. M and SD represent mean and standard deviation, respectively. Warning: Removed 1 rows containing non-finite values (stat_summary).
Removed 1 rows containing non-finite values (stat_summary).