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For this purpose, three types of relative evaluations are used: cross sectional, time series and panel data.
A panel data set consists of a cross sectional time series data in which attributes (e.g. Rainfall) of many units (e.g., Zones) are observed over time (e.g. Years).
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Table 3 presents the sectional times and whip counts in the three final 200 m sections.
Measurements of whip strikes and sectional times during each of the final three 200 metre (m) sections of five races were analysed.
Panel data (also known as longitudinal or cross sectional time-series data) is a dataset in which the behavior of entities (states, companies, individuals, countries, etc). is observed across time.
Whip counts and sectional times were used in this analysis.
There was also a significant interaction between race number and sectional times, (P<0.001).
Performances were described as total race times, 400 m, 200 m and final race placing and sectional times for S3, S2 and S1.
A split-plot repeated measures analysis of variance with a residual maximum likelihood (REML) algorithm was used to compare the three sectional times in the five races.
However, these scales are generally only appropriate for assessing a patient's state at a single cross-sectional time point.
Besides, the random parameters for cross-sectional time effects became nonsignificant when the thinning effects were specified in the fixed part of the model.
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