ctWideToLong Convert ctsem wide to long format
ctWideToLong Convert ctsem wide to long format
ctWideToLong( datawide, Tpoints, n.manifest, n.TDpred = 0, n.TIpred = 0, manifestNames = "auto", TDpredNames = "auto", TIpredNames = "auto" )
datawide |
ctsem wide format data |
Tpoints |
number of measurement occasions in data |
n.manifest |
number of manifest variables |
n.TDpred |
number of time dependent predictors |
n.TIpred |
number of time independent predictors |
manifestNames |
Character vector of manifest variable names. |
TDpredNames |
Character vector of time dependent predictor names. |
TIpredNames |
Character vector of time independent predictor names. |
Names must account for *all* the columns in the data - i.e. do not leave certain variables out just because you do not need them.
#create wide data
wideexample <- ctLongToWide(datalong = ctstantestdat, id = "id",
time = "time", manifestNames = c("Y1", "Y2"),
TDpredNames = "TD1", TIpredNames = c("TI1", "TI2","TI3"))
wide <- ctIntervalise(datawide = wideexample, Tpoints = 10, n.manifest = 2,
n.TDpred = 1, n.TIpred = 3, manifestNames = c("Y1", "Y2"),
TDpredNames = "TD1", TIpredNames = c("TI1", "TI2","TI3") )
#Then convert to long format
longexample <- ctWideToLong(datawide = wideexample, Tpoints=10,
n.manifest=2, manifestNames = c("Y1", "Y2"),
n.TDpred=1, TDpredNames = "TD1",
n.TIpred=3, TIpredNames = c("TI1", "TI2","TI3"))
#Then convert the time intervals to absolute time
long <- ctDeintervalise(datalong = longexample, id='id', dT='dT')
head(long,22)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.