Displaying 2 results from an estimated 2 matches for "vitclear".
2011 Apr 01
2
Cox Proportional Hazards model with a time-varying covariate
...1 5 0 C 4 . 332 10 1 C 3 .
333 16 0 C 3 . 334 -2 1 C 4 . 335 17 0 C 4 .
336 16 0 C 4 . 337 16 1 C 3 . 338 33 1 C 3 20
339 24 0 C 3 11 340 12 1 C 3 . 341 27 1 C 4 18
342 2 1 C 4 . 343 -6 0 C 4 . 344 -20 1 C 4 .
345 14 0 C 3 . 346 3 1 C 3 .
")
vitclear <- data.frame(scan(connection, na.strings=".",
list(PAT=0, RSPTIM=0, TRT=0, CENTER="", DENS=0, INFTIM=0)))
#RSPTIM = time (wks) from randomization to response (censored if negative)
#TRT = 1 for Hyalurise, TRT = 0 for Saline
#CENTER = study center (A, B, or C)
#DENS ...
2011 Jun 13
0
Setting up counting process data for survival analysis
...1 5 0 C 4 . 332 10 1 C 3 .
333 16 0 C 3 . 334 -2 1 C 4 . 335 17 0 C 4 .
336 16 0 C 4 . 337 16 1 C 3 . 338 33 1 C 3 20
339 24 0 C 3 11 340 12 1 C 3 . 341 27 1 C 4 18
342 2 1 C 4 . 343 -6 0 C 4 . 344 -20 1 C 4 .
345 14 0 C 3 . 346 3 1 C 3 .
")
vitclear <- data.frame(scan(connection, na.strings=".",
list(PAT=0, RSPTIM=0, TRT=0, CENTER="", DENS=0, INFTIM=0)))
head(vitclear)
connection <- textConnection("
PAT RSPTIM CENS TRT DENS CENTER T1 T2 INFCTN
101 2 0 1 3 A 0 2 0
101 4 0 1 3 A 2 4 0
101 6 0 1 3 A 4 6 0
101 7...