A previous analysis that excluded medium reward size trials showed the same statistical results on the main effect (data not presented in the manuscript).
A two-factor ANOVA revealed significant main effects of data type (real data vs. optimised data, F1,28 = 12.09, P < 0.01), a significant main effect of the dimension (layer vs. slice, F1,28 = 116.05, P < 0.001) and a significant interaction of data type and dimension (data type × dimension, F1,28 = 113.86, P < 0.001).
Since interactions were found to be statistically significant (results not shown) thus rendering the interpretation of main effects problematic, data was pooled across MOIs within each day.
A two-factor ANOVA showed a main effect of data type (real data vs. optimised data, F1,42 = 7.22, P < 0.05).
The main effect of data collection round (P < 0.05) on all weight, BMI and BMI/A Z-score values as well as on one W/A Z-score (6-year-old boys) and some H/A Z-score (7-year-old boys and 9-year-old girls) values were statistically significant.
Moreover, sensitivity analyses using different smoking exposure definitions (that is, defining exposure alternatively as 1) current, past, or never smoker, and 2) current or past/never smoker) did not reveal any further confounding of smoking on the main effect estimate (data not shown).
The blade flapping and the related drag are mentioned as the main effects introducing orientation data into the values provided by an accelerometer.
This method reflects the main effects in the data.
Three of the 10 interactions and three of the main effects from the imputed data models were not retained in the complete case model.
Temperature and semivolatile PM10 showed little association with 10-min odor ratings as main effects in mixed models (data not shown).
