| get_ind_time_matrix {santaR} | R Documentation |
Generate a Ind x Time DataFrame from input data
Description
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.
Usage
get_ind_time_matrix(Yi, ind, time, orderVect)
Arguments
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 |
Value
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.
See Also
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()
Examples
## 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)