Create longitudinal/panel data
addPeriods(
dtName,
nPeriods = NULL,
idvars = "id",
timevars = NULL,
timevarName = "timevar",
timeid = "timeID",
perName = "period",
periodVec = NULL
)Name of existing data table
Number of time periods for each record
Names of index variables (in a string vector) that will be repeated during each time period
Names of time dependent variables. Defaults to NULL.
Name of new time dependent variable
Variable name for new index field. Defaults to "timevar"
Variable name for period field. Defaults to "period"
Vector of period times. Defaults to NULL
An updated data.table that that has multiple rows per observation in dtName
It is possible to generate longitudinal data with varying numbers of measurement periods as well as varying time intervals between each measurement period. This is done by defining specific variables in the data set that define the number of observations per subject and the average interval time between each observation. nCount defines the number of measurements for an individual; mInterval specifies the average time between intervals for a subject; and vInterval specifies the variance of those interval times. If mInterval is not defined, no intervals are used. If vInterval is set to 0 or is not defined, the interval for a subject is determined entirely by the mean interval. If vInterval is greater than 0, time intervals are generated using a gamma distribution with specified mean and dispersion. If either nPeriods or timevars is specified, that will override any nCount, mInterval, and vInterval data.
periodVec is used to specify measurement periods that are different the default counting variables. If periodVec is not specified, the periods default to 0, 1, ... n-1, with n periods. If periodVec is specified as c(x_1, x_2, ... x_n), then x_1, x_2, ... x_n represent the measurement periods.
tdef <- defData(varname = "T", dist = "binary", formula = 0.5)
tdef <- defData(tdef, varname = "Y0", dist = "normal", formula = 10, variance = 1)
tdef <- defData(tdef, varname = "Y1", dist = "normal", formula = "Y0 + 5 + 5 * T", variance = 1)
tdef <- defData(tdef, varname = "Y2", dist = "normal", formula = "Y0 + 10 + 5 * T", variance = 1)
dtTrial <- genData(5, tdef)
dtTrial
#> Key: <id>
#> id T Y0 Y1 Y2
#> <int> <int> <num> <num> <num>
#> 1: 1 0 9.038907 13.77221 18.97153
#> 2: 2 0 9.402125 13.70966 19.96253
#> 3: 3 1 7.979656 18.63066 24.97564
#> 4: 4 1 9.500015 20.69839 24.42393
#> 5: 5 1 12.331997 22.71072 28.14005
dtTime <- addPeriods(dtTrial,
nPeriods = 3, idvars = "id",
timevars = c("Y0", "Y1", "Y2"), timevarName = "Y"
)
dtTime
#> Key: <timeID>
#> id period T Y timeID
#> <int> <int> <int> <num> <int>
#> 1: 1 0 0 9.038907 1
#> 2: 1 1 0 13.772206 2
#> 3: 1 2 0 18.971532 3
#> 4: 2 0 0 9.402125 4
#> 5: 2 1 0 13.709659 5
#> 6: 2 2 0 19.962525 6
#> 7: 3 0 1 7.979656 7
#> 8: 3 1 1 18.630661 8
#> 9: 3 2 1 24.975640 9
#> 10: 4 0 1 9.500015 10
#> 11: 4 1 1 20.698390 11
#> 12: 4 2 1 24.423926 12
#> 13: 5 0 1 12.331997 13
#> 14: 5 1 1 22.710725 14
#> 15: 5 2 1 28.140052 15
# Varying # of periods and intervals - need to have variables
# called nCount and mInterval
def <- defData(varname = "xbase", dist = "normal", formula = 20, variance = 3)
def <- defData(def, varname = "nCount", dist = "noZeroPoisson", formula = 6)
def <- defData(def, varname = "mInterval", dist = "gamma", formula = 30, variance = .01)
def <- defData(def, varname = "vInterval", dist = "nonrandom", formula = .07)
dt <- genData(200, def)
dt[id %in% c(8, 121)]
#> Key: <id>
#> id xbase nCount mInterval vInterval
#> <int> <num> <num> <num> <num>
#> 1: 8 19.52645 11 29.03541 0.07
#> 2: 121 18.53334 6 31.91971 0.07
dtPeriod <- addPeriods(dt)
dtPeriod[id %in% c(8, 121)] # View individuals 8 and 121 only
#> Key: <timeID>
#> id period xbase time timeID
#> <int> <int> <num> <num> <int>
#> 1: 8 0 19.52645 0 43
#> 2: 8 1 19.52645 25 44
#> 3: 8 2 19.52645 58 45
#> 4: 8 3 19.52645 78 46
#> 5: 8 4 19.52645 114 47
#> 6: 8 5 19.52645 138 48
#> 7: 8 6 19.52645 172 49
#> 8: 8 7 19.52645 208 50
#> 9: 8 8 19.52645 235 51
#> 10: 8 9 19.52645 272 52
#> 11: 8 10 19.52645 294 53
#> 12: 121 0 18.53334 0 744
#> 13: 121 1 18.53334 24 745
#> 14: 121 2 18.53334 65 746
#> 15: 121 3 18.53334 94 747
#> 16: 121 4 18.53334 129 748
#> 17: 121 5 18.53334 175 749