Results

Data from Muris et al. (2008). The authors investigated how children's tendency towards negative bias was affected by space-related training.

ANCOVA

ANCOVA - int_bias
Cases Sum of Squares df Mean Square F p ω²
scared 26400.360 1 26400.360 16.016 < .001 0.145
training 22129.485 1 22129.485 13.425 < .001 0.120
gender 11083.252 1 11083.252 6.724 0.012 0.055
age 2643.436 1 2643.436 1.604 0.210 0.006
Residuals 107146.585 65 1648.409  
Note.  Type III Sum of Squares

In the table above, we can see that even after partialling out the effects of age, gender and natural anxiety, the training had a significant effect on the subsequent bias score, F(1, 65) = 13.43, p < .001,  = .151 (95% CI: [0.027, 0.312]).

Descriptives

Descriptives - int_bias
training N Mean SD SE Coefficient of variation
Positive training 36 107.361 45.409 7.568 0.423
Negative training 34 145.912 48.699 8.352 0.334

The means tell us that interpretational biases were stronger (higher) after negative training. This result is as expected. It seems then that giving children feedback that tells them to interpret ambiguous situations negatively does induce an interpretational bias that persists into everyday situations, which is an important step towards understanding how these biases develop.

Linear Regression

Model Summary - int_bias
Model R Adjusted R² RMSE
M₀ 0.000 0.000 0.000 50.565
M₁ 0.627 0.393 0.355 40.601
Note.  M₁ includes training, gender, age, scared
Coefficients
95% CI
Model   Unstandardized Standard Error Standardizedᵃ t p Lower Upper
M₀ (Intercept) 126.086 6.044 20.863 < .001 114.029 138.142
M₁ (Intercept) 106.492 64.341 1.655 0.103 -22.007 234.991
  training (Negative training) 36.034 9.835 3.664 < .001 16.393 55.675
  gender 26.121 10.074 0.260 2.593 0.012 6.002 46.239
  age -7.278 5.747 -0.127 -1.266 0.210 -18.756 4.200
  scared 2.007 0.502 0.390 4.002 < .001 1.005 3.009
ᵃ Standardized coefficients can only be computed for continuous predictors.

In terms of the covariates, age did not have a significant influence on the acquisition of interpretational biases. However, anxiety and gender did. If we look at the Coefficients table, we can use the beta values to interpret these effects. For anxiety (scared), b = 2.01, which reflects a positive relationship. Therefore, as anxiety increases, the interpretational bias also increases (this is what you would expect, because anxious children would be more likely to naturally interpret ambiguous situations in a negative way). If you draw a scatterplot of the relationship between scared and int_bias you’ll see a very nice positive relationship. For genderb = 26.12, which again is positive, but to interpret this we need to know how the children were coded in the data editor. Boys were coded as 1 and girls as 2. Therefore, as a child ‘changes’ (not literally) from a boy to a girl, their interpretation biases increase. In other words, girls show a stronger natural tendency to interpret ambiguous situations negatively. This finidng is consistent with the anxiety literature, which shows that females are more likely to have anxiety disorders.


One important thing to remember is that although anxiety and gender naturally affected whether children interpreted ambiguous situations negatively, the training (the experiences on the alien planet) had an effect adjusting for these natural tendencies (in other words, the effects of training cannot be explained by gender or natural anxiety levels in the sample).


Have a look at the original article to see how Muris et al. reported the results of this analysis – this can help you to see how you can report your own data from an ANCOVA. (One bit of good practice that you should note is that they report effect sizes from their analysis – as you will see from the book chapter, this is an excellent thing to do.)


Correlation

Pearson's Correlations
Variable   gender age scared int_bias
1. gender Pearson's r
p-value      
2. age Pearson's r -0.229
p-value 0.057    
3. scared Pearson's r -0.059 -0.072
p-value 0.626 0.551  
4. int_bias Pearson's r 0.297 * -0.180 0.397 ***
p-value 0.012 0.137 < .001
* p < .05, ** p < .01, *** p < .001

Correlation plot