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Changes in AGB can be quantified by (1) comparing two observations in time (t 1 and t 2) with coincident field data to model change in biomass directly, with differences at the pixel level corresponding to remote sensing observables at t 1 and t 2, and (2) modelling AGB for t 1 and t 2 separately and taking the difference.
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In multilevel analyses, we used a compound symmetry covariance model with a two-level structure consisting of up to five observations in time (lower level) and the subject (higher level).
Table 2 reports the average rank changes in prices between two observations with a time lag of 1, 10, and 30 days in Barcelona, Madrid, Málaga, and Vigo.
The influence of previous observations decreases with increasing time between observations, i.e., if observations are made with large time interval, the influence of the previous observation will be small compared if two observations are made close in time.
Additionally, in order to assess 'expansion', observations at two points in time, at least, are required.
The small difference in the measurements at the two observation times indicated reproducibility of the method.
Towards this end, the position of the target individuals was recorded every 10 seconds over the 3 min test period, resulting in eighteen observation time points.
In our study, there is one observation in time (cross-sectional) with a recall item concerning economic stress in childhood, i.e. our study consists of references to only two observation points in time.
Two observations are, however, in order.
At times, observers would perform two observations consecutively.
Further observations were taken at two other points in time during each day over the same time period.
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CEO of Professional Science Editing for Scientists @ prosciediting.com