| get_ind_time_matrix | R Documentation | 
Convert input data with each measurement as a row, to a data.frame of measurements with Individual as rows and Time as columns. Pairs of Individual and Timepoint without a measurement are left as NA. The resulting data.frame is employed as input for santaR_fit.
get_ind_time_matrix(Yi, ind, time, orderVect)
| Yi | vector of measurements | 
| ind | vector of subject identifier (individual) corresponding to each measurement | 
| time | vector of time corresponding to each measurement | 
| orderVect | if provided, a vector of unique time to be used to order the time columns (otherwise rely on  | 
data.frame of measurements for each IND x TIME. Rows are unique Individual IDs and columns unique measurement Time. Pairs of (IND,TIME) without a measurement are left as NA.
Other Analysis: 
get_grouping(),
santaR_CBand(),
santaR_auto_fit(),
santaR_auto_summary(),
santaR_fit(),
santaR_plot(),
santaR_pvalue_dist(),
santaR_pvalue_fit(),
santaR_start_GUI()
## 6 measurements, 3 subjects, 3 unique time-points
Yi   <- c(1,2,3,4,5,6)
ind  <- c('ind_1','ind_1','ind_1','ind_2','ind_2','ind_3')
time <- c(0,5,10,0,10,5)
get_ind_time_matrix(Yi, ind, time)
#        0  5 10
# ind_1  1  2  3
# ind_2  4 NA  5
# ind_3 NA  6 NA
## 56 measurements, 8 subjects, 7 unique time-points
Yi   <- acuteInflammation$data$var_1
ind  <- acuteInflammation$meta$ind
time <- acuteInflammation$meta$time
get_ind_time_matrix(Yi, ind, time)
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