six independent variables for 2 x 2 x 2 factorial design
The p-values for these main effects, then you can see that the values are less than .0001. The F-statement and effect size of calculation for age of participant would be: F(1, 18) = 96.71 p < .0001.
- Data collected by researchers contributed to great extend in solving the research problem, initial data involved task duration, mental demand, number of task-related glances its duration, wheel velocity and several wheel reversal, etc. All these data collected affect the performance of participants in such a way that its adverse effects may consider, and it warns participants to be aware of the various difficulties that may arise if they do not.
However, reactions to surprise events that may happen while reading a message have not addressed here. Yet the mental demand of participants while driving is the main contribution of the researchers to the readers as people behave to the words in different ways depending on the state of mental conditions. Here the data collected is not proving towards people with various psychiatric conditions; instead, it assumes all participants have the same mental state during driving. This could be considered as a null hypothesis. In contrast, there are many factors analyzed here which contribute to drivers’ overall performance apart from the mental state like the vehicular conditions, visibility conditions of drivers, the physical state of drivers while sending and receiving text messages which could satisfy the needs of the alternate hypothesis.
The null and alternative hypothesis is indicated as in Anova test with F(1,18) which is maximum for modality and task alone, while different factors considered together F(1,18) is decreased drastically
Through first-order interaction, its implicated that each dependent measures have a decrease in its values, which indicates a positive nature towards drivers’ performance such that the dependent factors considered here are of adverse effects, and its result is detrimental. Hence, while pointing a low value means the first-order interaction observed for the hypothesis test is much appreciable. In the Anova test for hypothesis each value where critically determined and check for various factors like modality, task, age alone and then by choosing M X T, M X A, T X A, M X T X A
Where M is a modality
T is task
A is Age
- Internal validity contributed to the way they presented the results in a structured manner, like giving each factor based on material, task, and age. This had many subdivisions that satisfy the reader’s ability to identify and reconcile several elements with which the drivers’ performance could be analyzed for text messaging. Several factors were analyzed in a structured manner based on the three main factors; it included all the aspect that a driver may consider while text messaging in a vehicle including wheel turnings, glances, steering wheel velocities, etc. and we may know the importance of each single factors that may contribute to the driver’s performance during the journey.
External validity helped in such a manner that it was clearly understood that older group exhibited degradation of driving performance compared to younger groups, so there can be many factors that may keep in mind if older drivers are text messaging compared to younger once by adopting specific new devices and objects which may not question the performance of older drivers. Here sending of predetermined messages did not result in higher mental demand as well as an increase in the number of glances. Handheld devices contributed more to the degradation of performance. These are all the external validity in the study.