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Different frequencies of speed change and several RPM settings are compared.
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In general, mixing protocols with higher frequency of speed fluctuation produce the largest increase in stretching rates.
Significant gender*genotype effects were observed in centre and side speed, distance travelled, frequency of speed over 90 mm/s, immobility frequency and duration.
Table 7 presents the estimated results of the frequency of speeding model.
Higher income was significantly and negatively correlated with frequency of speeding when examined for observed behavior.
We divided the drivers into two groups: high frequency of speeding, including both those who reported speeding often or very often, and low frequency of speeding, including both those who reported speeding rarely or never.
Table 3 Degree of agreement with statements indicating risky behavior, in relation to the frequency of speeding Statement General sample High frequency (n = 54) (avg. ± s.d).
In addition, we did not find a significant correlation between the frequency of speeding and two continuous variables, age (p = 0.977) and driving experience (p = 0.116).
We also examined the association between categorical demographic variables and the frequency of speeding based on self-reporting, using a chi square test.
We found no significant correlations between self-reported frequency of speeding and the distance covered while speeding or between the duration of speeding and the perceived level of risk.
Table 4 Perceived contribution of different causes to the risk of being involved in a car crash in relation to the frequency of speeding Statement High frequency (n = 54) (avg. ± s.d).
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