Compute 24 Measures Describing the Features of the Trajectories
Computes 24 measures for each of the trajectories. See details for the list of measures.
A n by m matrix or data frame containing the values of each individual trajectory. Each row corresponds to one of the n trajectories, while the m columns correspond to the ordered values of a given trajectory. See details
A n by m matrix or data frame containing the measurement times corresponding to the values of the
Logical. Set to
Logical. Set to
There must be a minimum of 4 observations for each trajectory or the trajectory will be omitted from the analysis. The
trajectories do not need to have the same number of observations, nor the same values of
Time data.frame or matrix must have the same dimension as the
data frame or matrix and must not contain missing values or an error will be returned. The data can have missing values,
Time can not.
ID is set to
FALSE, a generic
ID variable is created and appended as the first
colunm of both the
The 24 measures are:
3. Standard deviation (SD)
4. Coefficient of variation (CV)
6. Mean change per unit time
7. Change relative to the first score
8. Change relative to the mean over time
9. Slope of the linear model*
10. R^2: Proportion of variance explained by the linear model
11. Maximum of the first differences
12. SD of the first differences
13. SD of the first differences per time unit
14. Mean of the absolute first differences*
15. Maximum of the absolute first differences
16. Ratio of the maximum absolute difference to the mean-over-time
17. Ratio of the maximum absolute first difference to the slope
18. Ratio of the SD of the first differences to the slope
19. Mean of the second differences
20. Mean of the absolute second differences
21. Maximum of the absolute second differences
22. Ration of the maximum absolute second difference to the mean-over-time
23. Ratio of the maximum absolute second difference to mean absolute first difference
24. Ratio of the mean absolute second difference to the mean absolute first difference
* If a measure is equal to zero, it will be set to the smallest, non-zero value of the same measure across the sample during further calculations. If Y_1, the first observation of the trajectory of an individual, is equal to zero, it will aslo be replaced.
For the exact equations of the measures, please go to "User guides, package vignettes and other documentation" section of the "traj" package.
Object containing the data used for the calculations and the 24 measures.
Marie-Pierre Sylvestre, Dan Vatnik
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# Setup data and time data = example.data$data time = example.data$time # Run step1measures s1 = step1measures(data,time, ID=TRUE) # Display measures head(s1$measurments) # Plot mean trajectory of all individuals plot(s1$measurments$ID, s1$measurments$m5) # The next step would be to run "step2factors"
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