Fit multiple spline regressions to the multiple required endpoints
Source:R/fitting-spl.R
fit_ends_mods_spl.RdFits multiple survival regressions, according to the distributions stipulated, to the multiple endpoints required in fitting partitioned survival analysis, clock forward and clock reset semi-markov models.
Usage
fit_ends_mods_spl(
simdat,
knot_set = 1:3,
scale_set = c("hazard", "odds", "normal"),
expvar = NA
)Arguments
- simdat
Dataset of patient level data. Must be a tibble with columns named:
ptid: patient identifier
pfs.durn: duration of PFS from baseline
pfs.flag: event flag for PFS (=1 if progression or death occurred, 0 for censoring)
os.durn: duration of OS from baseline
os.flag: event flag for OS (=1 if death occurred, 0 for censoring)
ttp.durn: duration of TTP from baseline (usually should be equal to pfs.durn)
ttp.flag: event flag for TTP (=1 if progression occurred, 0 for censoring).
Survival data for all other endpoints (time to progression, pre-progression death, post-progression survival) are derived from PFS and OS.
- knot_set
is a vector of the numbers of knots to consider, following
flexsurv::flexsurvspline()).- scale_set
is a vector of the spline scales to consider, following
flexsurv::flexsurvspline()).- expvar
Explanatory variable for modeling of PPS
Value
A list by endpoint, then distribution, each containing two components:
result: A list of class flexsurv::flexsurvspline containing information about the fitted model.
error: Any error message returned on fitting the regression (NULL indicates no error). Also, the given cuttime.
See also
Parametric modeling is handled by fit_ends_mods_par()
Examples
# \donttest{
# Create dataset in suitable form using bos dataset from the flexsurv package
bosonc <- create_dummydata("flexbosms")
fit_ends_mods_spl(bosonc, expvar=bosonc$ttp.durn)
#> $ttp
#> $ttp[[1]]
#> $ttp[[1]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.7114 -3.1392 -2.2836 0.2183
#> gamma1 0.9650 0.5632 1.3668 0.2050
#> gamma2 0.0110 -0.0211 0.0432 0.0164
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -422.8569, df = 3
#> AIC = 851.7137
#>
#>
#> $ttp[[1]]$error
#> NULL
#>
#>
#> $ttp[[2]]
#> $ttp[[2]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.8065 -3.2682 -2.3448 0.2356
#> gamma1 0.8694 0.4668 1.2720 0.2054
#> gamma2 -0.0153 -0.0511 0.0205 0.0183
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -421.7298, df = 3
#> AIC = 849.4597
#>
#>
#> $ttp[[2]]$error
#> NULL
#>
#>
#> $ttp[[3]]
#> $ttp[[3]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -1.60314 -1.83224 -1.37404 0.11689
#> gamma1 0.38216 0.20690 0.55743 0.08942
#> gamma2 -0.01936 -0.03709 -0.00163 0.00905
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -421.5655, df = 3
#> AIC = 849.1309
#>
#>
#> $ttp[[3]]$error
#> NULL
#>
#>
#> $ttp[[4]]
#> $ttp[[4]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.73940 -3.27510 -2.20370 0.27332
#> gamma1 0.94983 0.43830 1.46135 0.26098
#> gamma2 -0.00852 -0.14676 0.12973 0.07053
#> gamma3 0.02978 -0.19546 0.25502 0.11492
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -422.8021, df = 4
#> AIC = 853.6043
#>
#>
#> $ttp[[4]]$error
#> NULL
#>
#>
#> $ttp[[5]]
#> $ttp[[5]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.6568 -3.2137 -2.1000 0.2841
#> gamma1 1.0097 0.4700 1.5495 0.2754
#> gamma2 0.0691 -0.0964 0.2346 0.0844
#> gamma3 -0.1375 -0.4197 0.1448 0.1440
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -421.3791, df = 4
#> AIC = 850.7583
#>
#>
#> $ttp[[5]]$error
#> NULL
#>
#>
#> $ttp[[6]]
#> $ttp[[6]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -1.5359 -1.8178 -1.2539 0.1439
#> gamma1 0.4345 0.2068 0.6622 0.1162
#> gamma2 0.0304 -0.0583 0.1190 0.0452
#> gamma3 -0.0796 -0.2359 0.0768 0.0798
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -421.3112, df = 4
#> AIC = 850.6223
#>
#>
#> $ttp[[6]]$error
#> NULL
#>
#>
#> $ttp[[7]]
#> $ttp[[7]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.485963 -3.046933 -1.924993 0.286214
#> gamma1 1.197935 0.554813 1.841057 0.328130
#> gamma2 0.221183 0.000829 0.441538 0.112428
#> gamma3 -0.837151 -1.573248 -0.101055 0.375566
#> gamma4 0.887201 0.107971 1.666432 0.397574
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -420.1814, df = 5
#> AIC = 850.3627
#>
#>
#> $ttp[[7]]$error
#> NULL
#>
#>
#> $ttp[[8]]
#> $ttp[[8]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.4671 -3.0586 -1.8755 0.3018
#> gamma1 1.1985 0.5473 1.8496 0.3322
#> gamma2 0.2335 -0.0139 0.4809 0.1262
#> gamma3 -0.7797 -1.6893 0.1298 0.4641
#> gamma4 0.7355 -0.2786 1.7496 0.5174
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -420.0042, df = 5
#> AIC = 850.0085
#>
#>
#> $ttp[[8]]$error
#> NULL
#>
#>
#> $ttp[[9]]
#> $ttp[[9]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -1.4492 -1.7515 -1.1470 0.1542
#> gamma1 0.5042 0.2406 0.7677 0.1345
#> gamma2 0.1192 -0.0130 0.2514 0.0674
#> gamma3 -0.4462 -0.9748 0.0824 0.2697
#> gamma4 0.4287 -0.1742 1.0316 0.3076
#>
#> N = 204, Events: 103, Censored: 101
#> Total time at risk: 2358.845
#> Log-likelihood = -420.0067, df = 5
#> AIC = 850.0134
#>
#>
#> $ttp[[9]]$error
#> NULL
#>
#>
#>
#> $ppd
#> $ppd[[1]]
#> $ppd[[1]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -5.8254 -7.7259 -3.9250 0.9696
#> gamma1 1.5623 0.4569 2.6676 0.5640
#> gamma2 0.0167 -0.1170 0.1504 0.0682
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -153.7031, df = 3
#> AIC = 313.4063
#>
#>
#> $ppd[[1]]$error
#> NULL
#>
#>
#> $ppd[[2]]
#> $ppd[[2]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -5.79819 -7.70574 -3.89064 0.97326
#> gamma1 1.52049 0.39352 2.64746 0.57499
#> gamma2 -0.00446 -0.14762 0.13870 0.07304
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -154.0731, df = 3
#> AIC = 314.1461
#>
#>
#> $ppd[[2]]$error
#> NULL
#>
#>
#> $ppd[[3]]
#> $ppd[[3]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.7953 -3.4937 -2.0969 0.3563
#> gamma1 0.5645 0.1203 1.0088 0.2267
#> gamma2 -0.0331 -0.0986 0.0324 0.0334
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -154.0678, df = 3
#> AIC = 314.1356
#>
#>
#> $ppd[[3]]$error
#> NULL
#>
#>
#> $ppd[[4]]
#> $ppd[[4]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -6.260 -8.623 -3.897 1.206
#> gamma1 2.080 0.308 3.852 0.904
#> gamma2 0.404 -0.502 1.309 0.462
#> gamma3 -0.433 -1.434 0.569 0.511
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -153.3264, df = 4
#> AIC = 314.6528
#>
#>
#> $ppd[[4]]$error
#> NULL
#>
#>
#> $ppd[[5]]
#> $ppd[[5]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -6.279 -8.668 -3.891 1.219
#> gamma1 2.108 0.301 3.916 0.922
#> gamma2 0.487 -0.491 1.465 0.499
#> gamma3 -0.560 -1.666 0.545 0.564
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -153.5727, df = 4
#> AIC = 315.1455
#>
#>
#> $ppd[[5]]$error
#> NULL
#>
#>
#> $ppd[[6]]
#> $ppd[[6]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.920 -3.724 -2.115 0.410
#> gamma1 0.757 0.108 1.405 0.331
#> gamma2 0.207 -0.254 0.669 0.236
#> gamma3 -0.287 -0.839 0.266 0.282
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -153.6044, df = 4
#> AIC = 315.2088
#>
#>
#> $ppd[[6]]$error
#> NULL
#>
#>
#> $ppd[[7]]
#> $ppd[[7]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -6.3287 -8.9746 -3.6827 1.3500
#> gamma1 2.1917 -0.2409 4.6243 1.2411
#> gamma2 0.2345 -1.2648 1.7337 0.7649
#> gamma3 0.0531 -2.7173 2.8235 1.4135
#> gamma4 -0.3086 -2.3272 1.7101 1.0299
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -153.3243, df = 5
#> AIC = 316.6486
#>
#>
#> $ppd[[7]]$error
#> NULL
#>
#>
#> $ppd[[8]]
#> $ppd[[8]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -6.320 -8.969 -3.671 1.352
#> gamma1 2.182 -0.262 4.626 1.247
#> gamma2 0.223 -1.329 1.775 0.792
#> gamma3 0.174 -2.806 3.154 1.521
#> gamma4 -0.487 -2.746 1.772 1.153
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -153.5704, df = 5
#> AIC = 317.1408
#>
#>
#> $ppd[[8]]$error
#> NULL
#>
#>
#> $ppd[[9]]
#> $ppd[[9]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.89719 -3.73120 -2.06319 0.42552
#> gamma1 0.71931 -0.08609 1.52472 0.41093
#> gamma2 0.00886 -0.65672 0.67443 0.33959
#> gamma3 0.24938 -1.22124 1.71999 0.75033
#> gamma4 -0.38355 -1.60015 0.83305 0.62073
#>
#> N = 204, Events: 29, Censored: 175
#> Total time at risk: 2358.845
#> Log-likelihood = -153.5862, df = 5
#> AIC = 317.1723
#>
#>
#> $ppd[[9]]$error
#> NULL
#>
#>
#>
#> $pfs
#> $pfs[[1]]
#> $pfs[[1]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.71386 -3.13361 -2.29411 0.21416
#> gamma1 0.99398 0.61132 1.37664 0.19524
#> gamma2 0.00393 -0.01838 0.02623 0.01138
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -512.0123, df = 3
#> AIC = 1030.025
#>
#>
#> $pfs[[1]]$error
#> NULL
#>
#>
#> $pfs[[2]]
#> $pfs[[2]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.848058 -3.298634 -2.397482 0.229890
#> gamma1 0.832337 0.449968 1.214706 0.195090
#> gamma2 -0.025453 -0.051358 0.000453 0.013217
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -511.7148, df = 3
#> AIC = 1029.43
#>
#>
#> $pfs[[2]]$error
#> NULL
#>
#>
#> $pfs[[3]]
#> $pfs[[3]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -1.62401 -1.84681 -1.40122 0.11367
#> gamma1 0.37082 0.20155 0.54008 0.08636
#> gamma2 -0.02243 -0.03539 -0.00947 0.00661
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -511.4637, df = 3
#> AIC = 1028.927
#>
#>
#> $pfs[[3]]$error
#> NULL
#>
#>
#> $pfs[[4]]
#> $pfs[[4]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.7744 -3.2640 -2.2848 0.2498
#> gamma1 0.9271 0.4496 1.4046 0.2436
#> gamma2 -0.0307 -0.1621 0.1006 0.0670
#> gamma3 0.0441 -0.1240 0.2122 0.0858
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -511.8845, df = 4
#> AIC = 1031.769
#>
#>
#> $pfs[[4]]$error
#> NULL
#>
#>
#> $pfs[[5]]
#> $pfs[[5]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.7070 -3.2250 -2.1890 0.2643
#> gamma1 0.9774 0.4707 1.4841 0.2585
#> gamma2 0.0822 -0.0934 0.2577 0.0896
#> gamma3 -0.1403 -0.3779 0.0973 0.1212
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -511.2509, df = 4
#> AIC = 1030.502
#>
#>
#> $pfs[[5]]$error
#> NULL
#>
#>
#> $pfs[[6]]
#> $pfs[[6]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -1.5724 -1.8376 -1.3072 0.1353
#> gamma1 0.4129 0.1989 0.6270 0.1092
#> gamma2 0.0272 -0.0673 0.1217 0.0482
#> gamma3 -0.0637 -0.1942 0.0668 0.0666
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -511.2899, df = 4
#> AIC = 1030.58
#>
#>
#> $pfs[[6]]$error
#> NULL
#>
#>
#> $pfs[[7]]
#> $pfs[[7]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.5410 -3.0590 -2.0230 0.2643
#> gamma1 1.1468 0.5509 1.7427 0.3040
#> gamma2 0.1899 -0.0307 0.4104 0.1125
#> gamma3 -0.7089 -1.3939 -0.0238 0.3495
#> gamma4 0.6196 0.0378 1.2013 0.2968
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -509.8239, df = 5
#> AIC = 1029.648
#>
#>
#> $pfs[[7]]$error
#> NULL
#>
#>
#> $pfs[[8]]
#> $pfs[[8]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.5276 -3.0767 -1.9784 0.2802
#> gamma1 1.1501 0.5431 1.7570 0.3097
#> gamma2 0.2371 -0.0218 0.4960 0.1321
#> gamma3 -0.7336 -1.6567 0.1896 0.4710
#> gamma4 0.5475 -0.2959 1.3910 0.4303
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -510.0705, df = 5
#> AIC = 1030.141
#>
#>
#> $pfs[[8]]$error
#> NULL
#>
#>
#> $pfs[[9]]
#> $pfs[[9]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -1.4793 -1.7636 -1.1950 0.1450
#> gamma1 0.4844 0.2357 0.7330 0.1269
#> gamma2 0.1297 -0.0121 0.2716 0.0724
#> gamma3 -0.4727 -1.0114 0.0660 0.2749
#> gamma4 0.3763 -0.1221 0.8746 0.2543
#>
#> N = 204, Events: 132, Censored: 72
#> Total time at risk: 2358.845
#> Log-likelihood = -509.868, df = 5
#> AIC = 1029.736
#>
#>
#> $pfs[[9]]$error
#> NULL
#>
#>
#>
#> $os
#> $os[[1]]
#> $os[[1]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -5.0074 -6.2393 -3.7754 0.6286
#> gamma1 1.3996 0.7437 2.0556 0.3347
#> gamma2 -0.0157 -0.0995 0.0682 0.0428
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -433.2801, df = 3
#> AIC = 872.5603
#>
#>
#> $os[[1]]$error
#> NULL
#>
#>
#> $os[[2]]
#> $os[[2]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -4.8971 -6.1132 -3.6809 0.6205
#> gamma1 1.2418 0.5761 1.9075 0.3396
#> gamma2 -0.0854 -0.1808 0.0101 0.0487
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -435.5343, df = 3
#> AIC = 877.0686
#>
#>
#> $os[[2]]$error
#> NULL
#>
#>
#> $os[[3]]
#> $os[[3]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.5243 -3.0238 -2.0248 0.2549
#> gamma1 0.5252 0.2308 0.8195 0.1502
#> gamma2 -0.0771 -0.1250 -0.0292 0.0245
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -434.7993, df = 3
#> AIC = 875.5985
#>
#>
#> $os[[3]]$error
#> NULL
#>
#>
#> $os[[4]]
#> $os[[4]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -5.321 -6.770 -3.872 0.739
#> gamma1 1.745 0.799 2.692 0.483
#> gamma2 0.299 -0.208 0.807 0.259
#> gamma3 -0.402 -1.050 0.246 0.331
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -432.5721, df = 4
#> AIC = 873.1442
#>
#>
#> $os[[4]]$error
#> NULL
#>
#>
#> $os[[5]]
#> $os[[5]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -5.369 -6.851 -3.886 0.757
#> gamma1 1.807 0.817 2.797 0.505
#> gamma2 0.614 -0.020 1.249 0.324
#> gamma3 -0.930 -1.784 -0.076 0.436
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -433.4306, df = 4
#> AIC = 874.8611
#>
#>
#> $os[[5]]$error
#> NULL
#>
#>
#> $os[[6]]
#> $os[[6]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.6769 -3.2520 -2.1018 0.2934
#> gamma1 0.7502 0.3378 1.1625 0.2104
#> gamma2 0.3136 -0.0281 0.6553 0.1743
#> gamma3 -0.5287 -1.0036 -0.0538 0.2423
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -432.8091, df = 4
#> AIC = 873.6182
#>
#>
#> $os[[6]]$error
#> NULL
#>
#>
#> $os[[7]]
#> $os[[7]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -5.426 -6.984 -3.868 0.795
#> gamma1 1.879 0.738 3.019 0.582
#> gamma2 0.318 -0.573 1.209 0.455
#> gamma3 -0.275 -2.322 1.772 1.044
#> gamma4 -0.117 -1.820 1.587 0.869
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -432.4254, df = 5
#> AIC = 874.8508
#>
#>
#> $os[[7]]$error
#> NULL
#>
#>
#> $os[[8]]
#> $os[[8]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -5.4331 -7.0056 -3.8607 0.8023
#> gamma1 1.8919 0.7269 3.0570 0.5944
#> gamma2 0.3778 -0.6283 1.3840 0.5134
#> gamma3 0.0734 -2.4752 2.6220 1.3003
#> gamma4 -0.8477 -3.1700 1.4745 1.1848
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -433.2146, df = 5
#> AIC = 876.4292
#>
#>
#> $os[[8]]$error
#> NULL
#>
#>
#> $os[[9]]
#> $os[[9]]$result
#> Call:
#> .f(formula = ..1, k = ..2, scale = ..3)
#>
#> Estimates:
#> est L95% U95% se
#> gamma0 -2.6970 -3.2959 -2.0981 0.3056
#> gamma1 0.7819 0.3067 1.2570 0.2424
#> gamma2 0.1897 -0.3455 0.7250 0.2731
#> gamma3 0.0191 -1.4401 1.4784 0.7446
#> gamma4 -0.4670 -1.8384 0.9043 0.6997
#>
#> N = 204, Events: 97, Censored: 107
#> Total time at risk: 3479.143
#> Log-likelihood = -432.6368, df = 5
#> AIC = 875.2736
#>
#>
#> $os[[9]]$error
#> NULL
#>
#>
#>
#> $pps_cf
#> $pps_cf[[1]]
#> $pps_cf[[1]]$result
#> NULL
#>
#> $pps_cf[[1]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cf[[2]]
#> $pps_cf[[2]]$result
#> NULL
#>
#> $pps_cf[[2]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cf[[3]]
#> $pps_cf[[3]]$result
#> NULL
#>
#> $pps_cf[[3]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cf[[4]]
#> $pps_cf[[4]]$result
#> NULL
#>
#> $pps_cf[[4]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cf[[5]]
#> $pps_cf[[5]]$result
#> NULL
#>
#> $pps_cf[[5]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cf[[6]]
#> $pps_cf[[6]]$result
#> NULL
#>
#> $pps_cf[[6]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cf[[7]]
#> $pps_cf[[7]]$result
#> NULL
#>
#> $pps_cf[[7]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cf[[8]]
#> $pps_cf[[8]]$result
#> NULL
#>
#> $pps_cf[[8]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cf[[9]]
#> $pps_cf[[9]]$result
#> NULL
#>
#> $pps_cf[[9]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#>
#> $pps_cr
#> $pps_cr[[1]]
#> $pps_cr[[1]]$result
#> NULL
#>
#> $pps_cr[[1]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cr[[2]]
#> $pps_cr[[2]]$result
#> NULL
#>
#> $pps_cr[[2]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cr[[3]]
#> $pps_cr[[3]]$result
#> NULL
#>
#> $pps_cr[[3]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cr[[4]]
#> $pps_cr[[4]]$result
#> NULL
#>
#> $pps_cr[[4]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cr[[5]]
#> $pps_cr[[5]]$result
#> NULL
#>
#> $pps_cr[[5]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cr[[6]]
#> $pps_cr[[6]]$result
#> NULL
#>
#> $pps_cr[[6]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cr[[7]]
#> $pps_cr[[7]]$result
#> NULL
#>
#> $pps_cr[[7]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cr[[8]]
#> $pps_cr[[8]]$result
#> NULL
#>
#> $pps_cr[[8]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#> $pps_cr[[9]]
#> $pps_cr[[9]]$result
#> NULL
#>
#> $pps_cr[[9]]$error
#> <simpleError in model.frame.default(formula = survival::Surv(time = durn1, time2 = durn2, event = evflag) ~ { { expvar }}, data = <environment>): variable lengths differ (found for '{ { expvar } }')>
#>
#>
#>
# }