Related Experiment Video
Updated: May 22, 2026
06:53
Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
Published on: March 1, 2017
Sinuosity and the Affect Grid: a method for adjusting repeated mood scores.
Yvan I Russell1, Fernand Gobet
1Institute of Cognitive and Evolutionary Anthropology, University of Oxford, United Kingdom. yvanrussell@gmail.com
Perceptual and Motor Skills
|May 16, 2012
Summary
This study introduces a new sinuosity-based equation to correct mood measurements from the Affect Grid. It accounts for exaggerated mood shifts, reducing outliers in repeated mood assessments.
Area of Science:
- Psychology
- Hydrology
- Data Analysis
Background:
- The Affect Grid is a 9x9 mood scale measuring pleasure-displeasure and arousal-sleepiness.
- Repeated mood measurements can be affected by participant exaggeration or scale misinterpretation.
- Existing methods may not adequately address score inflation and outliers in mood data.
Purpose of the Study:
- To propose a novel equation for correcting mood measurements.
- To adapt sinuosity, a hydrological concept, for mood scale data analysis.
- To reduce outliers and correct for exaggerated mood shifts in Affect Grid data.
Main Methods:
- Applied sinuosity, a measure of pathway deviation from a straight line, to mood data.
- Developed a new equation incorporating sinuosity to account for exaggerated mood reporting.
- Validated the equation using Affect Grid data from a previous study.
Main Results:
- The proposed sinuosity-based equation effectively corrects mood scores.
- The method demonstrated utility in reducing outliers and mitigating exaggerated mood shifts.
- Application to existing Affect Grid data showed the equation's practical value.
Conclusions:
- Sinuosity offers a novel approach to refining mood measurement accuracy.
- The proposed equation enhances the reliability of repeated Affect Grid assessments.
- This method provides a valuable tool for analyzing psychological data with potential for response bias.
Related Concept Videos
01:24Design Example: Aggregate Gradation
The right type and quality of aggregates are crucial for concrete as they significantly influence its properties, mix proportions, and cost-effectiveness. If different sources are available for sand, the commonly used fine aggregate in concrete, the selection of sand is primarily based on its gradation.
The grading, or particle-size distribution, of sand is determined using sieve analysis, with standard sizes ranging from 150 μm to 10 mm (ASTM No. 100 sieve to 3⁄8 in. sieve). Sand is sampled...
The grading, or particle-size distribution, of sand is determined using sieve analysis, with standard sizes ranging from 150 μm to 10 mm (ASTM No. 100 sieve to 3⁄8 in. sieve). Sand is sampled...
01:06Skewness
The measures of central tendency calculated from a data set may not reveal much about its intrinsic distribution. If a plot is made of the data set’s values, the mean and the median may not only differ, but also the plot may have more values on one side of the central tendencies. Such a data set is said to be skewed towards that side.
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency are...
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency are...
01:09Harmonic Mean
The arithmetic mean is usually skewed towards the larger values in the data set. Therefore, to avoid this inherent bias towards smaller values, the harmonic mean is used.
Take the example of the speed of a car, which is the measure of the rate of distance traveled. If the vehicle traverses the same distance back-and-forth, its average speed equals the total distance traveled divided by the total time taken. However, if the car moves with varying speeds, then the arithmetic mean is more skewed...
Take the example of the speed of a car, which is the measure of the rate of distance traveled. If the vehicle traverses the same distance back-and-forth, its average speed equals the total distance traveled divided by the total time taken. However, if the car moves with varying speeds, then the arithmetic mean is more skewed...
01:17z Scores and Area Under the Curve
z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of zero.
01:28Simpson's Rule II
In warehouse roofing applications, corrugated or curved metal sheets are commonly used to improve structural strength, water drainage, and ventilation efficiency. To accurately estimate material requirements and optimize design parameters, engineers must determine the curved surface area of these sheets. Because the sheet profiles often repeat smoothly along their length, they can be effectively approximated by parabolic curves, enabling the use of numerical integration techniques for area...
01:26Unsoundness of Aggregate due to Volume Change
Unsoundness in aggregates due to volume changes is primarily caused by the physical alterations aggregates undergo, such as freezing and thawing, thermal changes, and wetting and drying. Unsound aggregates, when subjected to these changes, result in volume change upon disintegration. This, in turn, contributes to the deterioration of concrete, including scaling, pop-outs, and cracking. Particular types of aggregates, such as porous flints, cherts, and those containing clay minerals, are...