predict.coxph: Predictions for a Cox model

Description Usage Arguments Details Value Note See Also Examples

View source: R/predict.coxph.R

Description

Compute fitted values and regression terms for a model fitted by coxph

Usage

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## S3 method for class 'coxph'
predict(object, newdata,
type=c("lp", "risk", "expected", "terms", "survival"),
se.fit=FALSE, na.action=na.pass, terms=names(object$assign), collapse,
reference=c("strata", "sample", "zero"),  ...)

Arguments

object

the results of a coxph fit.

newdata

Optional new data at which to do predictions. If absent predictions are for the data frame used in the original fit. When coxph has been called with a formula argument created in another context, i.e., coxph has been called within another function and the formula was passed as an argument to that function, there can be problems finding the data set. See the note below.

type

the type of predicted value. Choices are the linear predictor ("lp"), the risk score exp(lp) ("risk"), the expected number of events given the covariates and follow-up time ("expected"), and the terms of the linear predictor ("terms"). The survival probability for a subject is equal to exp(-expected).

se.fit

if TRUE, pointwise standard errors are produced for the predictions.

na.action

applies only when the newdata argument is present, and defines the missing value action for the new data. The default is to include all observations. When there is no newdata, then the behavior of missing is dictated by the na.action option of the original fit.

terms

if type="terms", this argument can be used to specify which terms should be included; the default is all.

collapse

optional vector of subject identifiers. If specified, the output will contain one entry per subject rather than one entry per observation.

reference

reference for centering predictions, see details below

...

For future methods

Details

The Cox model is a relative risk model; predictions of type "linear predictor", "risk", and "terms" are all relative to the sample from which they came. By default, the reference value for each of these is the mean covariate within strata. The underlying reason is both statistical and practial. First, a Cox model only predicts relative risks between pairs of subjects within the same strata, and hence the addition of a constant to any covariate, either overall or only within a particular stratum, has no effect on the fitted results. Second, downstream calculations depend on the risk score exp(linear predictor), which will fall prey to numeric overflow for a linear predictor greater than .Machine\$double.max.exp. The coxph routines try to approximately center the predictors out of self protection. Using the reference="strata" option is the safest centering, since strata occassionally have different means. When the results of predict are used in further calculations it may be desirable to use a single reference level for all observations. Use of reference="sample" will use the overall means, and agrees with the linear.predictors component of the coxph object (which uses the overall mean for backwards compatability with older code). Predictions of type="terms" are almost invariably passed forward to further calculation, so for these we default to using the sample as the reference. A reference of "zero" causes no centering to be done.

Predictions of type "expected" incorporate the baseline hazard and are thus absolute instead of relative; the reference option has no effect on these. These values depend on the follow-up time for the future subjects as well as covariates so the newdata argument needs to include both the right and left hand side variables from the formula. (The status variable will not be used, but is required since the underlying code needs to reconstruct the entire formula.)

Models that contain a frailty term are a special case: due to the technical difficulty, when there is a newdata argument the predictions will always be for a random effect of zero.

Value

a vector or matrix of predictions, or a list containing the predictions (element "fit") and their standard errors (element "se.fit") if the se.fit option is TRUE.

Note

Some predictions can be obtained directly from the coxph object, and for others it is necessary for the routine to have the entirety of the original data set, e.g., for type = terms or if standard errors are requested. This extra information is saved in the coxph object if model=TRUE, if not the original data is reconstructed. If it is known that such residuals will be required overall execution will be slightly faster if the model information is saved.

In some cases the reconstruction can fail. The most common is when coxph has been called inside another function and the formula was passed as one of the arguments to that enclosing function. Another is when the data set has changed between the original call and the time of the prediction call. In each of these the simple solution is to add model=TRUE to the original coxph call.

See Also

predict,coxph,termplot

Examples

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options(na.action=na.exclude) # retain NA in predictions
fit <- coxph(Surv(time, status) ~ age + ph.ecog + strata(inst), lung)
#lung data set has status coded as 1/2
mresid <- (lung$status-1) - predict(fit, type='expected') #Martingale resid 
predict(fit,type="lp")
predict(fit,type="expected")
predict(fit,type="risk",se.fit=TRUE)
predict(fit,type="terms",se.fit=TRUE)

# For someone who demands reference='zero'
pzero <- function(fit)
  predict(fit, reference="sample") + sum(coef(fit) * fit$means, na.rm=TRUE)

Example output

           1            2            3            4            5            6 
 0.215495605 -0.423532231 -0.559265038  0.183469551 -0.539432878  0.248095483 
           7            8            9           10           11           12 
 0.406461814  0.489169379 -0.047448917  0.327284344  0.040389888  0.550315552 
          13           14           15           16           17           18 
-0.115925255           NA  0.055807340  0.110906025  0.050567124  0.493760215 
          19           20           21           22           23           24 
 0.557645717 -0.004245606 -0.127236322 -0.621260082 -0.319524466 -0.575882288 
          25           26           27           28           29           30 
-0.345688084  0.202851214 -0.428371074  1.313400384 -0.021210624  0.761244928 
          31           32           33           34           35           36 
 0.191540147  0.749933860  0.180240469  0.459827013  0.672213041  0.625512121 
          37           38           39           40           41           42 
 0.565173220  0.085767683  0.761244928  0.076972823  0.330513426  0.511791514 
          43           44           45           46           47           48 
-0.439682141  0.660901974 -0.164699618  0.496950353 -0.381077937  0.091073865 
          49           50           51           52           53           54 
-0.354839644 -0.175654221  0.192873470 -0.447487689 -0.450985298 -0.562055013 
          55           56           57           58           59           60 
 0.063012023 -0.516810744 -0.297203343  0.474684682  0.034518529  0.076972823 
          61           62           63           64           65           66 
 0.678283893 -0.045992266  0.176731471 -0.149858457  0.158940268  0.718790633 
          67           68           69           70           71           72 
 0.539004484 -0.308514410 -0.543216443  0.153500561 -0.479261384 -0.078592144 
          73           74           75           76           77           78 
 0.946919127 -0.073531430 -0.049489875  0.214162281 -0.641232484  0.029078821 
          79           80           81           82           83           84 
-0.276488357 -0.392389004 -0.439682141  0.001411510 -0.410013004 -0.151289480 
          85           86           87           88           89           90 
-0.292311495  0.198744830 -0.039921414 -0.530162769 -0.123010230  0.738622793 
          91           92           93           94           95           96 
-0.743642023  0.050567124  0.285269157  0.108857156 -0.437633273  0.796634781 
          97           98           99          100          101          102 
 0.158940268  0.214162281 -0.161169524 -0.400910096 -0.562055013  0.176122695 
         103          104          105          106          107          108 
 0.012722577  0.108256292  0.617817211  0.157606945 -0.189452466  0.110906025 
         109          110          111          112          113          114 
-0.026867740  0.797968104 -0.411394980 -0.149248522  0.369011703 -0.344354760 
         115          116          117          118          119          120 
 0.006456686  0.783867062  0.503880355  0.693378524  0.527693417  0.244122624 
         121          122          123          124          125          126 
-0.464038972  0.449575370  0.158940268  0.500480446 -0.426322206  0.005322855 
         127          128          129          130          131          132 
-0.368298829  0.134984810  0.652115157 -0.617153698  0.131479291 -0.190511890 
         133          134          135          136          137          138 
-0.643882217  0.001411510 -0.460255408  0.666972826  0.067118407  0.583884010 
         139          140          141          142          143          144 
-0.036137850 -0.399002948  0.747892903  0.215495605  0.630552446  0.088283890 
         145          146          147          148          149          150 
-0.240346995 -0.200763533 -0.558074111 -0.179200822 -0.232577411 -0.524505653 
         151          152          153          154          155          156 
 0.171077519 -0.633704981 -0.331136545 -0.190511890  0.477441161           NA 
         157          158          159          160          161          162 
-0.031097524  0.736573925  0.123673743 -0.013515715 -0.585704233 -0.038186718 
         163          164          165          166          167          168 
 0.466547245  0.108256292 -0.209943887 -0.716429053 -0.206413793 -0.699828778 
         169          170          171          172          173          174 
 0.085634157 -0.424865554  0.069277914 -0.441093652  0.107445646 -0.874783994 
         175          176          177          178          179          180 
-0.047448917  0.046655779  0.557645717  0.001411510 -0.047448917 -0.667994646 
         181          182          183          184          185          186 
-0.513194586 -0.776965291 -0.614629447  0.019390401 -0.583220496 -0.651086900 
         187          188          189          190          191          192 
 0.859584155 -0.536642904  0.063145548 -0.712882451  0.024398388  0.369338475 
         193          194          195          196          197          198 
-0.023370131  0.076972823  0.061878192 -0.368310218 -0.003231734  0.074931865 
         199          200          201          202          203          204 
-0.629921417 -0.037164935  0.063145548  0.084500326 -0.574393166 -0.627131442 
         205          206          207          208          209          210 
-0.658814293  0.302547317 -0.410314015  0.516017606  0.131487202 -0.302547317 
         211          212          213          214          215          216 
-0.539432878  0.153500561  0.119700884  0.409991908 -0.149858457 -0.149858457 
         217          218          219          220          221          222 
-0.156943432  0.781826105  0.477858312 -0.452404719  0.016633922 -0.081992053 
         223          224          225          226          227          228 
 0.212705630  0.224016697 -0.750726998  0.703662506  0.142189494 -0.085165683 
         1          2          3          4          5          6          7 
0.74602570 0.57892506 1.28411487 0.65144995 2.53474317 2.59935704 0.94925558 
         8          9         10         11         12         13         14 
1.07812821 0.63137435 0.55866807 0.31809979 1.96068120 2.96879741         NA 
        15         16         17         18         19         20         21 
2.14464916 0.39248100 1.01652225 2.53985878 0.23734050 0.15454932 0.41781121 
        22         23         24         25         26         27         28 
0.03725873 1.07425239 0.73304358 0.71922541 1.96068538 0.91425760 0.50868712 
        29         30         31         32         33         34         35 
1.07651355 0.10727131 1.64348011 0.22335391 1.34246079 0.18355514 0.25427967 
        36         37         38         39         40         41         42 
0.57948554 3.87217595 1.42062915 0.50341133 2.84274107 1.90670187 0.39302876 
        43         44         45         46         47         48         49 
1.67374788 0.56009982 1.95081502 0.39930277 0.62185372 1.18384892 1.08920268 
        50         51         52         53         54         55         56 
1.36922169 2.72429090 0.31557423 0.04821232 0.41960993 3.07164840 0.12000994 
        57         58         59         60         61         62         63 
0.07406041 0.17908976 1.74520134 1.10195998 1.47697029 0.54523697 0.51461493 
        64         65         66         67         68         69         70 
0.14292300 0.18117365 0.20227027 0.70028855 1.00636733 0.31133532 0.64126839 
        71         72         73         74         75         76         77 
0.96177399 0.46743320 0.53451717 0.16345589 0.86294287 1.44797843 1.06953116 
        78         79         80         81         82         83         84 
1.19014609 0.03668315 0.33061179 1.90397464 0.08944145 0.20857044 0.28585781 
        85         86         87         88         89         90         91 
1.15723874 0.87295638 1.19851949 0.14216346 1.37338069 0.92021616 1.05096221 
        92         93         94         95         96         97         98 
0.27465006 0.47403241 0.26750987 1.01622540 0.08901343 0.32456045 0.93961618 
        99        100        101        102        103        104        105 
0.85179714 0.14362313 0.89733451 1.74403467 0.70225748 0.15754565 0.36065915 
       106        107        108        109        110        111        112 
0.41227011 0.29089093 0.02759911 2.54485283 1.57705739 0.02915789 0.51482474 
       113        114        115        116        117        118        119 
1.51254632 0.24392791 1.95773713 0.16855572 0.69132758 2.65613080 1.04014324 
       120        121        122        123        124        125        126 
0.89157179 0.40187641 0.23829273 1.56065440 0.17535194 1.02778525 0.18442460 
       127        128        129        130        131        132        133 
0.08051722 0.20596405 1.70473379 0.86354367 0.72017118 0.27146814 0.48487446 
       134        135        136        137        138        139        140 
1.10114414 0.51567846 1.46035831 0.93950468 1.54314328 1.12143879 0.60372302 
       141        142        143        144        145        146        147 
1.46022571 0.88081136 0.66047105 0.18347489 0.51981101 0.28761918 0.50825077 
       148        149        150        151        152        153        154 
0.15268490 0.06671446 0.32571666 0.39746179 0.39772440 0.38939509 0.20940447 
       155        156        157        158        159        160        161 
0.62171971         NA 0.34080256 0.46159657 0.47539058 1.00662370 0.21472196 
       162        163        164        165        166        167        168 
0.54619593 0.50111574 0.24481910 0.51248548 0.19954882 0.25566706 0.78817717 
       169        170        171        172        173        174        175 
0.44798249 0.43113659 0.44847984 1.48341994 0.46620310 0.37028208 0.86812344 
       176        177        178        179        180        181        182 
0.43844817 0.94494334 0.25935783 0.37625255 0.20649507 0.25048304 0.37569346 
       183        184        185        186        187        188        189 
0.40334526 0.39324727 0.36799524 0.39552828 1.77501387 0.24422514 0.38021709 
       190        191        192        193        194        195        196 
0.21501843 0.51818689 0.08032921 0.22774986 0.71502728 0.36774267 0.39500663 
       197        198        199        200        201        202        203 
0.38445105 0.97727710 0.43520510 0.16869554 0.17219830 0.05878035 0.21716448 
       204        205        206        207        208        209        210 
0.18384556 0.18192355 0.64682101 0.35975276 0.70106697 1.03414013 0.35317899 
       211        212        213        214        215        216        217 
0.42921059 0.47944086 0.40234009 0.25017393 0.04470913 0.27054309 0.22137404 
       218        219        220        221        222        223        224 
1.18698635 0.50681607 0.11190719 0.11327702 0.28954125 0.33611081 0.74776723 
       225        226        227        228 
0.12225025 0.00000000 0.35218786 0.10231300 
$fit
        1         2         3         4         5         6         7         8 
1.2404765 0.6547301 0.5716290 1.2013784 0.5830788 1.2815823 1.5014958 1.6309609 
        9        10        11        12        13        14        15        16 
0.9536592 1.3871959 1.0412167 1.7338000 0.8905418        NA 1.0573939 1.1172899 
       17        18        19        20        21        22        23        24 
1.0518675 1.6384656 1.7465558 0.9957634 0.8805256 0.5372670 0.7264944 0.5622086 
       25        26        27        28        29        30        31        32 
0.7077332 1.2248902 0.6515696 3.7187976 0.9790127 2.1409399 1.2111135 2.1168600 
       33        34        35        36        37        38        39        40 
1.1975053 1.5838000 1.9585669 1.8692030 1.7597526 1.0895532 2.1409399 1.0800127 
       41        42        43        44        45        46        47        48 
1.3916825 1.6682773 0.6442412 1.9365383 0.8481484 1.6437009 0.6831246 1.0953499 
       49        50        51        52        53        54        55        56 
0.7012859 0.8389080 1.2127293 0.6392321 0.6370002 0.5700364 1.0650396 0.5964197 
       57        58        59        60        61        62        63        64 
0.7428929 1.6075072 1.0351212 1.0800127 1.9704933 0.9550493 1.1933106 0.8608298 
       65        66        67        68        69        70        71        72 
1.1722679 2.0519501 1.7142994 0.7345374 0.5808769 1.1659084 0.6192406 0.9244169 
       73        74        75        76        77        78        79        80 
2.5777557 0.9291069 0.9517148 1.2388237 0.5266429 1.0295057 0.7584424 0.6754413 
       81        82        83        84        85        86        87        88 
0.6442412 1.0014125 0.6636416 0.8595988 0.7465360 1.2198707 0.9608649 0.5885092 
       89        90        91        92        93        94        95        96 
0.8842546 2.0930510 0.4753794 1.0518675 1.3301200 1.1150031 0.6455625 2.2180641 
       97        98        99       100       101       102       103       104 
1.1722679 1.2388237 0.8511478 0.6697103 0.5700364 1.1925844 1.0128039 1.1143333 
      105       106       107       108       109       110       111       112 
1.8548748 1.1707060 0.8274120 1.1172899 0.9734900 2.2210235 0.6627251 0.8613550 
      113       114       115       116       117       118       119       120 
1.4463045 0.7086775 1.0064776 2.1899245 1.6551313 2.0004627 1.6950181 1.2765009 
      121       122       123       124       125       126       127       128 
0.6287391 1.5676464 1.1722679 1.6495136 0.6529059 1.0053370 0.6919104 1.1445194 
      129       130       131       132       133       134       135       136 
1.9195968 0.5394778 1.1405143 0.8265359 0.5252493 1.0014125 0.6311224 1.9483304 
      137       138       139       140       141       142       143       144 
1.0694221 1.7929889 0.9645073 0.6709887 2.1125440 1.2404765 1.8786481 1.0922982 
      145       146       147       148       149       150       151       152 
0.7863550 0.8181059 0.5723102 0.8359380 0.7924884 0.5918479 1.1865827 0.5306222 
      153       154       155       156       157       158       159       160 
0.7181071 0.8265359 1.6119444        NA 0.9693810 2.0887670 1.1316466 0.9865752 
      161       162       163       164       165       166       167       168 
0.5567137 0.9625332 1.5944793 1.1143333 0.8106297 0.4884935 0.8134964 0.4966703 
      169       170       171       172       173       174       175       176 
1.0894077 0.6538577 1.0717340 0.6433325 1.1134303 0.4169521 0.9536592 1.0477613 
      177       178       179       180       181       182       183       184 
1.7465558 1.0014125 0.9536592 0.5127358 0.5985803 0.4597993 0.5408413 1.0195796 
      185       186       187       188       189       190       191       192 
0.5580981 0.5214787 2.3621782 0.5847079 1.0651819 0.4902291 1.0246985 1.4467772 
      193       194       195       196       197       198       199       200 
0.9769008 1.0800127 1.0638328 0.6919025 0.9967735 1.0778107 0.5326337 0.9635172 
      201       202       203       204       205       206       207       208 
1.0651819 1.0881732 0.5630464 0.5341218 0.5174645 1.3533017 0.6634419 1.6753425 
      209       210       211       212       213       214       215       216 
1.1405233 0.7389335 0.5830788 1.1659084 1.1271597 1.5068056 0.8608298 0.8608298 
      217       218       219       220       221       222       223       224 
0.8547524 2.1854595 1.6126170 0.6360967 1.0167730 0.9212793 1.2370205 1.2510919 
      225       226       227       228 
0.4720233 2.0211416 1.1527951 0.9183601 

$se.fit
          1           2           3           4           5           6 
0.094027169 0.096340319 0.096185061 0.110144705 0.091221886 0.124003567 
          7           8           9          10          11          12 
0.106470052 0.135893441 0.104263809 0.115204660 0.048057506 0.157626321 
         13          14          15          16          17          18 
0.058398830          NA 0.078593550 0.044525715 0.047523899 0.139753275 
         19          20          21          22          23          24 
0.246130195 0.051683778 0.050651208 0.106747848 0.121191090 0.095563151 
         25          26          27          28          29          30 
0.135232494 0.077970827 0.084316589 0.541641696 0.047411370 0.244541270 
         31          32          33          34          35          36 
0.067316853 0.236761412 0.222247496 0.143779967 0.246770836 0.214866749 
         37          38          39          40          41          42 
0.186808694 0.027994134 0.244541270 0.017746688 0.094899948 0.150429986 
         43          44          45          46          47          48 
0.082038635 0.251128992 0.071539989 0.172653479 0.157627962 0.046664065 
         49          50          51          52          53          54 
0.203630081 0.147427688 0.071868116 0.087051165 0.126710133 0.091078334 
         55          56          57          58          59          60 
0.030346404 0.094111921 0.072518580 0.232795318 0.092391388 0.017746688 
         61          62          63          64          65          66 
0.207337260 0.162712161 0.126511646 0.038549743 0.042876315 0.234595146 
         67          68          69          70          71          72 
0.151669341 0.068462840 0.112880428 0.068678027 0.124246473 0.184637680 
         73          74          75          76          77          78 
0.325442016 0.174862073 0.090441588 0.089040153 0.108376599 0.057550307 
         79          80          81          82          83          84 
0.188633743 0.150191651 0.082038635 0.027564795 0.181878087 0.172125872 
         85          86          87          88          89          90 
0.142365056 0.114741553 0.035859182 0.096819023 0.132484179 0.229864932 
         91          92          93          94          95          96 
0.120689668 0.047523899 0.070339929 0.055381362 0.123547581 0.253870138 
         97          98          99         100         101         102 
0.042876315 0.089040153 0.035190905 0.106227011 0.091078334 0.091298269 
        103         104         105         106         107         108 
0.017787711 0.028641480 0.194430169 0.039989624 0.075782969 0.044525715 
        109         110         111         112         113         114 
0.071209628 0.254965259 0.163546509 0.185211877 0.241649528 0.139074790 
        115         116         117         118         119         120 
0.076796420 0.262556790 0.348185429 0.211911041 0.146845572 0.149423594 
        121         122         123         124         125         126 
0.150969692 0.156065943 0.042876315 0.142648758 0.129688202 0.004890619 
        127         128         129         130         131         132 
0.113985419 0.031310085 0.248637733 0.121183075 0.041502912 0.067248608 
        133         134         135         136         137         138 
0.115359144 0.027564795 0.112511267 0.200585657 0.069255092 0.201817172 
        139         140         141         142         143         144 
0.094786456 0.075667327 0.240338975 0.094027169 0.216098624 0.024974398 
        145         146         147         148         149         150 
0.066191299 0.084423319 0.167625233 0.058808327 0.221289168 0.105873833 
        151         152         153         154         155         156 
0.140449741 0.098993713 0.063583542 0.067248608 0.230942129          NA 
        157         158         159         160         161         162 
0.067558237 0.245408761 0.032338223 0.075589234 0.101745759 0.174851413 
        163         164         165         166         167         168 
0.125897325 0.028641480 0.048065722 0.111659253 0.045260623 0.125085448 
        169         170         171         172         173         174 
0.020095538 0.093808006 0.037378627 0.093118562 0.031761359 0.135544076 
        175         176         177         178         179         180 
0.104263809 0.016586035 0.246130195 0.027564795 0.104263809 0.174088607 
        181         182         183         184         185         186 
0.109727836 0.166211707 0.139230772 0.017941579 0.106388490 0.137198131 
        187         188         189         190         191         192 
0.304795981 0.089505183 0.043311645 0.114439474 0.131445121 0.192173147 
        193         194         195         196         197         198 
0.144436340 0.017746688 0.058484070 0.121193159 0.002956631 0.025613128 
        199         200         201         202         203         204 
0.104623286 0.033429233 0.043311645 0.080773833 0.103942128 0.124008736 
        205         206         207         208         209         210 
0.118294076 0.078206752 0.080505144 0.235804861 0.079727031 0.057789591 
        211         212         213         214         215         216 
0.091221886 0.068678027 0.029421496 0.124248857 0.038549743 0.038549743 
        217         218         219         220         221         222 
0.158976598 0.269332667 0.130275218 0.089792820 0.015369862 0.085131550 
        223         224         225         226         227         228 
0.148494109 0.160862263 0.138362860 0.225740927 0.057778343 0.074788433 

$fit
             age     ph.ecog
1    0.130878057  0.03032716
2    0.063011653 -0.54083428
3   -0.072721154 -0.54083428
4   -0.061410086  0.03032716
5   -0.027476885 -0.54083428
6    0.130878057  0.03032716
7    0.063011653  0.60148859
8    0.096944855  0.60148859
9   -0.106654355  0.03032716
10  -0.016165817  0.60148859
11  -0.061410086  0.03032716
12   0.063011653  0.60148859
13   0.063011653  0.03032716
14            NA          NA
15  -0.061410086  0.03032716
16   0.051700586  0.03032716
17   0.085633788  0.03032716
18   0.006456317  0.60148859
19  -0.072721154  0.60148859
20  -0.061410086  0.03032716
21   0.051700586  0.03032716
22  -0.151898625 -0.54083428
23  -0.140587557  0.03032716
24  -0.050099019 -0.54083428
25   0.108255923 -0.54083428
26   0.085633788  0.03032716
27  -0.027476885 -0.54083428
28   0.085633788  1.17265002
29  -0.106654355  0.03032716
30   0.130878057  0.60148859
31   0.074322721  0.03032716
32   0.119566990  0.60148859
33  -0.163209692  0.60148859
34  -0.027476885  0.60148859
35  -0.016165817  0.60148859
36  -0.004854750  0.60148859
37   0.029078452  0.60148859
38   0.040389519  0.03032716
39   0.130878057  0.60148859
40   0.017767384  0.03032716
41   0.085633788  0.03032716
42   0.119566990  0.60148859
43  -0.038787952 -0.54083428
44  -0.027476885  0.60148859
45   0.063011653  0.03032716
46   0.153500192  0.60148859
47   0.130878057 -0.54083428
48   0.006456317  0.03032716
49   0.130878057 -0.54083428
50  -0.140587557  0.03032716
51   0.108255923  0.03032716
52   0.006456317 -0.54083428
53   0.063011653 -0.54083428
54  -0.050099019 -0.54083428
55  -0.038787952  0.03032716
56  -0.004854750 -0.54083428
57   0.029078452 -0.54083428
58  -0.061410086  0.60148859
59  -0.050099019  0.03032716
60   0.017767384  0.03032716
61   0.142189124  0.60148859
62  -0.163209692  0.03032716
63   0.119566990  0.03032716
64   0.029078452  0.03032716
65   0.074322721  0.03032716
66   0.063011653  0.60148859
67   0.051700586  0.60148859
68   0.017767384 -0.54083428
69   0.063011653 -0.54083428
70   0.051700586  0.03032716
71   0.006456317 -0.54083428
72  -0.163209692  0.03032716
73   0.130878057  0.60148859
74  -0.253698230  0.03032716
75  -0.106654355  0.03032716
76   0.096944855  0.03032716
77  -0.129276490 -0.54083428
78  -0.072721154  0.03032716
79   0.210055528 -0.54083428
80   0.119566990 -0.54083428
81  -0.038787952 -0.54083428
82  -0.084032221  0.03032716
83  -0.231076095  0.03032716
84  -0.208453961  0.03032716
85  -0.208453961  0.03032716
86   0.096944855  0.03032716
87  -0.004854750  0.03032716
88  -0.016165817 -0.54083428
89  -0.208453961  0.03032716
90   0.108255923  0.60148859
91   0.006456317 -0.54083428
92   0.085633788  0.03032716
93   0.040389519  0.03032716
94  -0.061410086  0.03032716
95   0.074322721 -0.54083428
96   0.108255923  0.60148859
97   0.074322721  0.03032716
98   0.096944855  0.03032716
99   0.017767384  0.03032716
100  0.085633788 -0.54083428
101 -0.050099019 -0.54083428
102  0.074322721  0.03032716
103 -0.072721154  0.03032716
104  0.006456317  0.03032716
105 -0.038787952  0.60148859
106  0.040389519  0.03032716
107 -0.095343288  0.03032716
108  0.051700586  0.03032716
109 -0.084032221  0.03032716
110  0.142189124  0.60148859
111  0.074322721 -0.54083428
112 -0.208453961  0.03032716
113  0.198744461  0.03032716
114  0.142189124 -0.54083428
115 -0.095343288  0.03032716
116  0.153500192  0.60148859
117 -0.151898625  0.60148859
118  0.063011653  0.60148859
119  0.040389519  0.60148859
120  0.198744461  0.03032716
121  0.142189124 -0.54083428
122 -0.027476885  0.60148859
123  0.074322721  0.03032716
124  0.108255923  0.60148859
125  0.085633788 -0.54083428
126  0.040389519  0.03032716
127 -0.140587557  0.03032716
128  0.017767384  0.03032716
129  0.164811259  0.60148859
130 -0.163209692 -0.54083428
131 -0.038787952  0.03032716
132 -0.106654355  0.03032716
133 -0.174520759 -0.54083428
134 -0.084032221  0.03032716
135  0.051700586 -0.54083428
136  0.130878057  0.60148859
137 -0.050099019  0.03032716
138 -0.072721154  0.60148859
139 -0.095343288  0.03032716
140 -0.072721154 -0.54083428
141  0.119566990  0.60148859
142  0.130878057  0.03032716
143  0.153500192  0.60148859
144  0.029078452  0.03032716
145 -0.061410086  0.03032716
146 -0.106654355  0.03032716
147  0.096944855 -0.54083428
148 -0.095343288  0.03032716
149  0.221366595 -0.54083428
150 -0.038787952 -0.54083428
151  0.085633788  0.03032716
152 -0.027476885 -0.54083428
153 -0.004854750 -0.54083428
154 -0.106654355  0.03032716
155 -0.084032221  0.60148859
156           NA          NA
157  0.063011653  0.03032716
158 -0.004854750  0.60148859
159  0.006456317  0.03032716
160 -0.072721154  0.03032716
161 -0.004854750 -0.54083428
162 -0.208453961  0.03032716
163  0.074322721  0.60148859
164  0.006456317  0.03032716
165  0.017767384  0.03032716
166 -0.061410086 -0.54083428
167 -0.027476885  0.03032716
168 -0.185831826 -0.54083428
169 -0.016165817  0.03032716
170  0.029078452 -0.54083428
171 -0.016165817  0.03032716
172 -0.050099019 -0.54083428
173 -0.072721154  0.03032716
174 -0.219765028 -0.54083428
175 -0.106654355  0.03032716
176 -0.038787952  0.03032716
177 -0.072721154  0.60148859
178 -0.084032221  0.03032716
179 -0.106654355  0.03032716
180  0.130878057 -0.54083428
181 -0.027476885 -0.54083428
182 -0.265009297 -0.54083428
183  0.040389519 -0.54083428
184  0.029078452  0.03032716
185 -0.129276490 -0.54083428
186 -0.197142894 -0.54083428
187  0.108255923  0.60148859
188 -0.050099019 -0.54083428
189  0.017767384  0.03032716
190 -0.106654355 -0.54083428
191  0.108255923  0.03032716
192 -0.117965423  0.60148859
193 -0.140587557  0.03032716
194  0.017767384  0.03032716
195  0.096944855  0.03032716
196  0.085633788 -0.54083428
197  0.006456317  0.03032716
198  0.017767384  0.03032716
199 -0.117965423 -0.54083428
200 -0.027476885  0.03032716
201  0.017767384  0.03032716
202  0.119566990  0.03032716
203  0.006456317 -0.54083428
204 -0.140587557 -0.54083428
205  0.006456317 -0.54083428
206 -0.004854750  0.60148859
207 -0.084032221 -0.54083428
208 -0.140587557  0.60148859
209  0.074322721  0.03032716
210 -0.038787952  0.03032716
211 -0.027476885 -0.54083428
212  0.051700586  0.03032716
213  0.074322721  0.03032716
214  0.017767384  0.60148859
215  0.029078452  0.03032716
216  0.029078452  0.03032716
217 -0.242387163  0.03032716
218  0.153500192  0.60148859
219  0.085633788  0.60148859
220 -0.061410086 -0.54083428
221  0.051700586  0.03032716
222  0.096944855  0.03032716
223  0.153500192  0.03032716
224  0.164811259  0.03032716
225 -0.265009297 -0.54083428
226  0.142189124  0.60148859
227  0.040389519  0.03032716
228 -0.050099019  0.03032716

$se.fit
            age     ph.ecog
1   0.119930635 0.007395102
2   0.057740983 0.131879319
3   0.066638322 0.131879319
4   0.056273380 0.007395102
5   0.025178554 0.131879319
6   0.119930635 0.007395102
7   0.057740983 0.146669523
8   0.088835809 0.146669523
9   0.097733148 0.007395102
10  0.014813612 0.146669523
11  0.056273380 0.007395102
12  0.057740983 0.146669523
13  0.057740983 0.007395102
14           NA          NA
15  0.056273380 0.007395102
16  0.047376041 0.007395102
17  0.078470867 0.007395102
18  0.005916272 0.146669523
19  0.066638322 0.146669523
20  0.056273380 0.007395102
21  0.047376041 0.007395102
22  0.139192917 0.131879319
23  0.128827975 0.007395102
24  0.045908438 0.131879319
25  0.099200751 0.131879319
26  0.078470867 0.007395102
27  0.025178554 0.131879319
28  0.078470867 0.285943945
29  0.097733148 0.007395102
30  0.119930635 0.146669523
31  0.068105925 0.007395102
32  0.109565693 0.146669523
33  0.149557859 0.146669523
34  0.025178554 0.146669523
35  0.014813612 0.146669523
36  0.004448670 0.146669523
37  0.026646156 0.146669523
38  0.037011098 0.007395102
39  0.119930635 0.146669523
40  0.016281214 0.007395102
41  0.078470867 0.007395102
42  0.109565693 0.146669523
43  0.035543496 0.131879319
44  0.025178554 0.146669523
45  0.057740983 0.007395102
46  0.140660519 0.146669523
47  0.119930635 0.131879319
48  0.005916272 0.007395102
49  0.119930635 0.131879319
50  0.128827975 0.007395102
51  0.099200751 0.007395102
52  0.005916272 0.131879319
53  0.057740983 0.131879319
54  0.045908438 0.131879319
55  0.035543496 0.007395102
56  0.004448670 0.131879319
57  0.026646156 0.131879319
58  0.056273380 0.146669523
59  0.045908438 0.007395102
60  0.016281214 0.007395102
61  0.130295577 0.146669523
62  0.149557859 0.007395102
63  0.109565693 0.007395102
64  0.026646156 0.007395102
65  0.068105925 0.007395102
66  0.057740983 0.146669523
67  0.047376041 0.146669523
68  0.016281214 0.131879319
69  0.057740983 0.131879319
70  0.047376041 0.007395102
71  0.005916272 0.131879319
72  0.149557859 0.007395102
73  0.119930635 0.146669523
74  0.232477395 0.007395102
75  0.097733148 0.007395102
76  0.088835809 0.007395102
77  0.118463033 0.131879319
78  0.066638322 0.007395102
79  0.192485229 0.131879319
80  0.109565693 0.131879319
81  0.035543496 0.131879319
82  0.077003264 0.007395102
83  0.211747511 0.007395102
84  0.191017627 0.007395102
85  0.191017627 0.007395102
86  0.088835809 0.007395102
87  0.004448670 0.007395102
88  0.014813612 0.131879319
89  0.191017627 0.007395102
90  0.099200751 0.146669523
91  0.005916272 0.131879319
92  0.078470867 0.007395102
93  0.037011098 0.007395102
94  0.056273380 0.007395102
95  0.068105925 0.131879319
96  0.099200751 0.146669523
97  0.068105925 0.007395102
98  0.088835809 0.007395102
99  0.016281214 0.007395102
100 0.078470867 0.131879319
101 0.045908438 0.131879319
102 0.068105925 0.007395102
103 0.066638322 0.007395102
104 0.005916272 0.007395102
105 0.035543496 0.146669523
106 0.037011098 0.007395102
107 0.087368206 0.007395102
108 0.047376041 0.007395102
109 0.077003264 0.007395102
110 0.130295577 0.146669523
111 0.068105925 0.131879319
112 0.191017627 0.007395102
113 0.182120287 0.007395102
114 0.130295577 0.131879319
115 0.087368206 0.007395102
116 0.140660519 0.146669523
117 0.139192917 0.146669523
118 0.057740983 0.146669523
119 0.037011098 0.146669523
120 0.182120287 0.007395102
121 0.130295577 0.131879319
122 0.025178554 0.146669523
123 0.068105925 0.007395102
124 0.099200751 0.146669523
125 0.078470867 0.131879319
126 0.037011098 0.007395102
127 0.128827975 0.007395102
128 0.016281214 0.007395102
129 0.151025461 0.146669523
130 0.149557859 0.131879319
131 0.035543496 0.007395102
132 0.097733148 0.007395102
133 0.159922801 0.131879319
134 0.077003264 0.007395102
135 0.047376041 0.131879319
136 0.119930635 0.146669523
137 0.045908438 0.007395102
138 0.066638322 0.146669523
139 0.087368206 0.007395102
140 0.066638322 0.131879319
141 0.109565693 0.146669523
142 0.119930635 0.007395102
143 0.140660519 0.146669523
144 0.026646156 0.007395102
145 0.056273380 0.007395102
146 0.097733148 0.007395102
147 0.088835809 0.131879319
148 0.087368206 0.007395102
149 0.202850171 0.131879319
150 0.035543496 0.131879319
151 0.078470867 0.007395102
152 0.025178554 0.131879319
153 0.004448670 0.131879319
154 0.097733148 0.007395102
155 0.077003264 0.146669523
156          NA          NA
157 0.057740983 0.007395102
158 0.004448670 0.146669523
159 0.005916272 0.007395102
160 0.066638322 0.007395102
161 0.004448670 0.131879319
162 0.191017627 0.007395102
163 0.068105925 0.146669523
164 0.005916272 0.007395102
165 0.016281214 0.007395102
166 0.056273380 0.131879319
167 0.025178554 0.007395102
168 0.170287743 0.131879319
169 0.014813612 0.007395102
170 0.026646156 0.131879319
171 0.014813612 0.007395102
172 0.045908438 0.131879319
173 0.066638322 0.007395102
174 0.201382569 0.131879319
175 0.097733148 0.007395102
176 0.035543496 0.007395102
177 0.066638322 0.146669523
178 0.077003264 0.007395102
179 0.097733148 0.007395102
180 0.119930635 0.131879319
181 0.025178554 0.131879319
182 0.242842337 0.131879319
183 0.037011098 0.131879319
184 0.026646156 0.007395102
185 0.118463033 0.131879319
186 0.180652685 0.131879319
187 0.099200751 0.146669523
188 0.045908438 0.131879319
189 0.016281214 0.007395102
190 0.097733148 0.131879319
191 0.099200751 0.007395102
192 0.108098090 0.146669523
193 0.128827975 0.007395102
194 0.016281214 0.007395102
195 0.088835809 0.007395102
196 0.078470867 0.131879319
197 0.005916272 0.007395102
198 0.016281214 0.007395102
199 0.108098090 0.131879319
200 0.025178554 0.007395102
201 0.016281214 0.007395102
202 0.109565693 0.007395102
203 0.005916272 0.131879319
204 0.128827975 0.131879319
205 0.005916272 0.131879319
206 0.004448670 0.146669523
207 0.077003264 0.131879319
208 0.128827975 0.146669523
209 0.068105925 0.007395102
210 0.035543496 0.007395102
211 0.025178554 0.131879319
212 0.047376041 0.007395102
213 0.068105925 0.007395102
214 0.016281214 0.146669523
215 0.026646156 0.007395102
216 0.026646156 0.007395102
217 0.222112453 0.007395102
218 0.140660519 0.146669523
219 0.078470867 0.146669523
220 0.056273380 0.131879319
221 0.047376041 0.007395102
222 0.088835809 0.007395102
223 0.140660519 0.007395102
224 0.151025461 0.007395102
225 0.242842337 0.131879319
226 0.130295577 0.146669523
227 0.037011098 0.007395102
228 0.045908438 0.007395102

survival documentation built on Aug. 24, 2021, 5:06 p.m.