ex1 {Epi} | R Documentation |
Splits follow-up time at prespecified points of follow-up.
ex1( enter, exit, fail, origin = 0, scale = 1, breaks, data = data.frame(enter, exit, fail), Expand = 1:nrow(data) )
enter |
Date of entry einto the study (start of follow-up). Numeric. |
exit |
Date of termination of follow-up. Numeric. |
fail |
Status at exit from the study. |
origin |
Origin of the timescale to split on. Specified on the
input timescale, i.e. that of enter and exit . |
scale |
Scaling between input and analysis timescale. |
breaks |
Breakpoints on the analysis timescale. Follow-up before
min(breaks) and and ater max(breks) is discarded. |
data |
Dataframe of variables to carry over to the output. |
Expand |
Variable identifying original records. |
If entry
and exit
are given in days (for example as
Date
variables, and we want follow-up cut at 5-year age
intervals, the we should choose origin
equal to bithdate, scale
equal to 365.25 and breaks as seq(0,100,5)
. Thus the input
timescale is calendar tiem measured in days, and output timescale is
age measured in years.
A dataframe with one row per follow-up interval, and variables as in
data
, preceded by the variables:
Expand |
Identification of the rows from the input dataframe. |
Enter |
Entry date for the interval. |
Exit |
Exit date for the interval. |
Fail |
Failure indicator for end of the current interval. |
Bendix Carstensen, Steno Diabetes Center, bxc@steno.dk, www.biostat.ku.dk/~bxc
one <- round( runif( 15, 0, 10 ), 1 ) two <- round( runif( 15, 0, 10 ), 1 ) doe <- pmin( one, two ) dox <- pmax( one, two ) # Goofy data rows to test possibly odd behaviour doe[1:3] <- dox[1:3] <- 8 dox[2] <- 6 dox[3] <- 7.5 # Some failure indicators fail <- sample( 0:1, 15, replace=TRUE, prob=c(0.7,0.3) ) # Split follow-up: ex1( doe, dox, fail, breaks=0:10 )