https://github.com/cran/rstpm2
Tip revision: c12a9847539968aa375d4df8349a3a524e7c1bb5 authored by Mark Clements on 17 January 2019, 14:50:04 UTC
version 1.4.5
version 1.4.5
Tip revision: c12a984
timevar2.html
<?xml version="1.0" encoding="utf-8"?> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"> <head> <meta http-equiv="Content-Type" content="text/html;charset=utf-8"/> <meta name="viewport" content="width=device-width, initial-scale=1"/> <title>Predictions</title> <meta name="generator" content="Org-mode"/> <meta name="author" content="Mark Clements"/> <style type="text/css"> .title{ text-align:center;margin-bottom:.2em;}.subtitle{ text-align:center;font-size:medium;font-weight:bold;margin-top:0;}.todo{ font-family:monospace;color:red;}.done{ font-family:monospace;color:green;}.priority{ font-family:monospace;color:orange;}.tag{ background-color:#eee;font-family:monospace;padding:2px;font-size:80%;font-weight:normal;}.timestamp{ color:#bebebe;}.timestamp-kwd{ color:#5f9ea0;}.org-right{ margin-left:auto;margin-right:0px;text-align:right;}.org-left{ margin-left:0px;margin-right:auto;text-align:left;}.org-center{ margin-left:auto;margin-right:auto;text-align:center;}.underline{ text-decoration:underline;}#postamble p, #preamble p{ font-size:90%;margin:.2em;}p.verse{ margin-left:3%;}pre{ border:1px solid #ccc;box-shadow:3px 3px 3px #eee;padding:8pt;font-family:monospace;overflow:auto;margin:1.2em;}pre.src{ position:relative;overflow:visible;padding-top:1.2em;}pre.src:before{ display:none;position:absolute;background-color:white;top:-10px;right:10px;padding:3px;border:1px solid black;}pre.src:hover:before{ display:inline;}pre.src-sh:before{ content:'sh';}pre.src-bash:before{ content:'sh';}pre.src-emacs-lisp:before{ content:'Emacs Lisp';}pre.src-R:before{ content:'R';}pre.src-perl:before{ content:'Perl';}pre.src-java:before{ content:'Java';}pre.src-sql:before{ content:'SQL';}table{ border-collapse:collapse;}caption.t-above{ caption-side:top;}caption.t-bottom{ caption-side:bottom;}td, th{ vertical-align:top;}th.org-right{ text-align:center;}th.org-left{ text-align:center;}th.org-center{ text-align:center;}td.org-right{ text-align:right;}td.org-left{ text-align:left;}td.org-center{ text-align:center;}dt{ font-weight:bold;}.footpara{ display:inline;}.footdef{ margin-bottom:1em;}.figure{ padding:1em;}.figure p{ text-align:center;}.inlinetask{ padding:10px;border:2px solid gray;margin:10px;background:#ffffcc;}#org-div-home-and-up{ text-align:right;font-size:70%;white-space:nowrap;}textarea{ overflow-x:auto;}.linenr{ font-size:smaller }.code-highlighted{ background-color:#ffff00;}.org-info-js_info-navigation{ border-style:none;}#org-info-js_console-label{ font-size:10px;font-weight:bold;white-space:nowrap;}.org-info-js_search-highlight{ background-color:#ffff00;color:#000000;font-weight:bold;}--> </style> <script type="text/javascript">function CodeHighlightOn(e,a){var c=document.getElementById(a);null!=c&&(e.cacheClassElem=e.className,e.cacheClassTarget=c.className,c.className="code-highlighted",e.className="code-highlighted")}function CodeHighlightOff(e,a){var c=document.getElementById(a);e.cacheClassElem&&(e.className=e.cacheClassElem),e.cacheClassTarget&&(c.className=e.cacheClassTarget)}</script> </head> <body> <div id="content"> <h1 class="title">Predictions</h1> <div id="outline-container-orgheadline1" class="outline-2"> <h2 id="orgheadline1"><span class="section-number-2">1</span> R implementation for <a href="https://pclambert.net/software/stpm2/stpm2_timevar/">https://pclambert.net/software/stpm2/stpm2_timevar/</a></h2> <div class="outline-text-2" id="text-1"> <div class="org-src-container"> <pre class="src src-R"><span style="color:#008b8b;">library(rstpm2)
<span style="color:#008b8b;">library(readstata13)
suppressWarnings(rott2b <span style="color:#008b8b;"><- read.dta13(<span style="color:#8b2252;">"https://www.pclambert.net/data/rott2b.dta"))
rott2b <span style="color:#008b8b;"><- transform(rott2b, time = pmin(rf,60)/12)
rott2b <span style="color:#008b8b;"><- transform(rott2b, event = (rfi==1) & (time < 60/12))
fit <span style="color:#008b8b;"><- stpm2(Surv(time,event) ~ hormon + nsx(age,df=3,centre=60,stata=<span style="color:#228b22;">TRUE) + pr_1,
data=rott2b, df=4, stata=<span style="color:#228b22;">TRUE)
eform(fit)
</span style="color:#228b22;"></span style="color:#228b22;"></span style="color:#008b8b;"></span style="color:#008b8b;"></span style="color:#008b8b;"></span style="color:#8b2252;"></span style="color:#008b8b;"></span style="color:#008b8b;"></span style="color:#008b8b;"></pre> </div> <pre class="example">
Profiling...
exp(beta) 2.5 % 97.5 %
(Intercept) 6.055607e-04 5.715701e-04 6.402896e-04
hormonyes 1.253597e+00 1.065865e+00 1.462097e+00
nsx(age, df = 3, centre = 60, stata = TRUE)1 6.550003e-01 5.594371e-01 7.702334e-01
nsx(age, df = 3, centre = 60, stata = TRUE)2 3.449221e-01 1.993938e-01 5.962187e-01
nsx(age, df = 3, centre = 60, stata = TRUE)3 9.626652e-01 7.189637e-01 1.275743e+00
pr_1 9.080228e-01 8.944134e-01 9.214805e-01
nsx(log(time), df = 4)1 4.474345e+02 4.148646e+02 4.799754e+02
nsx(log(time), df = 4)2 1.974220e+02 1.894423e+02 2.047062e+02
nsx(log(time), df = 4)3 5.391834e+04 4.862060e+04 5.986957e+04
nsx(log(time), df = 4)4 7.282589e+01 6.949526e+01 7.650186e+01
</pre> <div class="org-src-container"> <pre class="src src-R">nd <span style="color:#008b8b;"><- data.frame(age=60, hormon=<span style="color:#8b2252;">"no", pr_1=0)
plot(fit, type=<span style="color:#8b2252;">"surv", newdata=nd, xlab=<span style="color:#8b2252;">"Years from surgery")
</span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#008b8b;"></pre> </div> <div class="figure"> <p><img 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" alt="surv_1.png"/> </p> </div> <div class="org-src-container"> <pre class="src src-R">nd <span style="color:#008b8b;"><- data.frame(age=60, hormon=<span style="color:#8b2252;">"no", pr_1=0)
plot(fit, type=<span style="color:#8b2252;">"haz", newdata=transform(nd, hormon=<span style="color:#8b2252;">"yes"), xlab=<span style="color:#8b2252;">"Years from surgery",
line.col=<span style="color:#8b2252;">"blue", rug=<span style="color:#228b22;">FALSE)
lines(fit, type=<span style="color:#8b2252;">"haz", newdata=nd, col=<span style="color:#8b2252;">"red")
</span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#228b22;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#008b8b;"></pre> </div> <div class="figure"> <p><img 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" alt="haz_1.png"/> </p> </div> <div class="org-src-container"> <pre class="src src-R">s_time1 <span style="color:#008b8b;"><- predict(fit, newdata=transform(rott2b, time=1), type=<span style="color:#8b2252;">"surv")
hist(s_time1,xlab=<span style="color:#8b2252;">"Time from surgery",main=<span style="color:#8b2252;">"")
</span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#008b8b;"></pre> </div> <div class="figure"> <p><img src="data:image/png;base64,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" alt="histo_1.png"/> </p> </div> <div class="org-src-container"> <pre class="src src-R">s_time5 <span style="color:#008b8b;"><- predict(fit, newdata=transform(rott2b, time=5), type=<span style="color:#8b2252;">"surv")
hist(s_time5,xlab=<span style="color:#8b2252;">"Time from surgery",main=<span style="color:#8b2252;">"")
</span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#008b8b;"></pre> </div> <div class="figure"> <p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAeAAAAHgCAMAAABKCk6nAAACzVBMVEUAAAABAQECAgIDAwMEBAQFBQUHBwcICAgJCQkKCgoLCwsMDAwNDQ0ODg4PDw8QEBARERESEhITExMUFBQVFRUWFhYXFxcYGBgZGRkaGhobGxscHBwdHR0eHh4fHx8gICAhISEiIiIjIyMkJCQlJSUmJiYnJycoKCgpKSkqKiorKyssLCwtLS0uLi4vLy8wMDAxMTEyMjIzMzM0NDQ1NTU3Nzc4ODg5OTk6Ojo7Ozs8PDw9PT0+Pj4/Pz9AQEBBQUFCQkJDQ0NERERFRUVGRkZHR0dISEhJSUlKSkpMTExNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1eXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2tsbGxtbW1ubm5vb29wcHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t9fX1+fn5/f3+AgICCgoKDg4OEhISGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCSkpKTk5OUlJSVlZWYmJiZmZmbm5ucnJydnZ2enp6fn5+goKChoaGioqKlpaWnp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCxsbGysrKzs7O0tLS1tbW2tra3t7e5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fIyMjJycnKysrLy8vMzMzOzs7Pz8/Q0NDR0dHS0tLT09PW1tbX19fY2NjZ2dna2trb29vc3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7////+Z3b+AAAQg0lEQVR4nO3di39U5Z3H8UiQYkIDBA0J2uzSRKxsghSbpUqBbrC2tQqauKuloqyttrXV9UJrGyouEaT0YkNL3YqiIl3cqqkCrRhLUqFrbOUi5SbmJiqQkMvzN3RmMjbJzDnT38k5c/LMj8/n9ZLEme95Mrze3IZcyDKkuqyRfgCU3gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBnPZeqxW2Kx1vHeC09+BD9aL+e2U63jrAae/BF2S75wDOzABWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKAzhDO9ok6xvPyc4D2LKuvemroqY8JDsPYMta1CbbVdbKdgBbFsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ioB7j/em421neFqAT9WUjs7KLlnemY43n8lpAV68YFvr6bYdC29Jx5vP5LQA5x2JvTgxKR1vPpPTAjxjfezFppnpePOZnBbgxsKLq5dWlxU1pePNZ3JagE13fV1tXX13Ot56RqcGmKdJzmkB5mmSS1qAeZrkkhbg5KdJ25bF+urGdDygzEkLcPLTpJb+L3S9ck06HlDmpAXY9WnSE4+k4wFlTlqAXZ8mASzbWQ8c7Z325NsAlu1sB35j3u4DFdlnz/lr4h0Ay3a2A1fc1XnNHac67/184h0Ay3a2A+e+bUreNObd3MQ7AJbtbAdesKbv1jpjNlySeAfAsp3twIc+ddGXRs2bm78j8Q6AZTvbgY3Z9avVP9l8MulmgGU7+4FdAli2AzhDA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ACsPYOUBrDyAlQew8gBWHsDKA1h5ANtV5w1Vsr4jPBBgu2q9ql3WZ4QHAmxXrdcKh/OEO4DtCmCvASzbARxOAHsNYNkO4HAC2GsAy3YAh5MYuGSZrGlHZecBHE5i4I82yTr3Tdl5AIeTGHi8cDcFYKsC2GsAy3YAhxPAXgNYtgM4nAD2GsCyHcDhBLDXAJbtAA4ngL0GsGwHcDgB7DWAZTuAwwlgrwEs2wEcTgB7DWDZDuBwAthrAMt2AIcTwF4DWLYDOJwA9hrAsh3A4QSw1wCW7QAOJ4C9BrBsB3A4Aew1gGU7gMPpzAa+Y3uP50sBlu2sAK4pL7j9xW5vlwIs21kBbMzeNXMKbn3+tIdLAZbtLAHu2LhkwvTZRZvklwIs21kBvGpuzhU/3mfM1snySwGW7awAvvnp92IvP+BnsE7grkfqzTOrO11Gvcd7HW4FWLazAvgrn2w0uy6/2WlxqqZ0dFZ2yfIkfYBlOyuAc/dGvjmQ57RYvGBb6+m2HQtvSbwDYNnOCuCPvxr5pmGq0yLvSOzFiUmJdwAs21kBvCH/jofvnPSo02LG+tiLTTMT7wBYtrMC2LzxwNdqdjkuGgsvrl5aXVbUlHgHwLKdHcAp6q6vq62rT/57TIBlOyuAfzt7WjSXEU+TnMoo4I8t+//mSE4Lnia5lFHAhSddFzxNcimjgFevdH1fYfLTpKcqY5XfnY4HlLbObODLcsZd6PJ7ME+TXMoo4Ob+nBY8TXIpo4CN6TnS5zLhaZJzGQV8pHJs7v6Kve67huT3NAEs21kB/B+3nSjorfms+y7/YNJNAMt2VgBP7DAFpv0cp0VOdrSsUdmJdwAs21kBXL4lAvzSdKfF67Or9ra0TNjdkngHwLKdFcDb8q8bu+Tc5xwnPWun/R+/RCeXUcCm9dEV6464jfbM+/I4gBPLLODU9dZd35p0I8CynRXAFf15uhRg2c4K4IaGhlc2zt3o6VKAZTsrgGO1zfB0KcCynT3Au8Z5uhRg2c4K4OhvwLNG3+npUoBlOyuAG6I1u727wTmAZTsrgIcTwLKdFcBTxufFk18KsGxnBfDP5r18pKHyRx0dHfJLAZbtrAA+/1Dkm7fP93QpwLKdFcAX/C7yzY4iT5cCLNtZAVw38TvrvjvxIU+XAizbWQFs/vBf13+znqdJ0XQCp/igO7cAlu2sAP6HH3TnEMCynRXA//CD7hwCWLazAjjFB925BrBsZwVwig+6cw1g2c4K4FQfdOcWwLKdFcCpP+jOOYBlOyuAy/7k/VKAZTsrgFfc3uX5UoBlOyuA5+aNK3H/Gh3OASzbWQGc4vODXQNYtrMAOKfDmMfe93opwLKdBcBZEeC8/V4vBVi2AzicAPZ6KcCynQ3ALzU25vy6sbHR06UAy3YWAOd/mKdLAZbtLAAeXgDLdgCHE8BeA1i2AzicAPYawLIdwOEEsNcAlu0ADieAvQawbAdwOAHsNYBlO4DDCWCvASzbARxOAHsNYNkO4HAC2GsAy3YAhxPAXgNYtgM4nAD2GsCyHcDhBLDXAJbtAA4ngL0GsGwHcDgB7DWAZTuAwwlgrwEs2wEcTgB7DWDZDuBwAthrAMt2AIcTwF4DWLYDOJwAdq/3eK/DrQDLdrYDn6opHZ2VXbK8M/EOgGU724EXL9jWerptx8JbEu8AWLazHTiv/wvBn5iUeAfAsp3twDPWx15smpl4B8Cyne3AjYUXVy+tLitqSrwDYNnOdmDTXV9XW1ffnXQ7wLKd9cA8TXJOCzBPk1zSApz8NGnfxlh3CR+4JQHsUvLTpJ21sW78QToekOeaLq0UNadUeOCZBmz706QXHpTt3pwiPPBMA7b9aRLAKcv8p0kAp0zyNKk9+o+/97Qk3gywbGc78OvTz5q6xZj9SUuAZTvbgT/z/a7tUxoBTkoL8Nj3jNk8qwfgxLQAX/isMX3X3A9wYlqAn8m9/JhpmXkJwAlpATZHn4n8It35+H2JtwMs21kP7BbAsh3A/gI4ZQAnBXA8gGU7gP0FcMoATgrgeADLdgD7C+CUAZwUwPEAlu0A9hfAKQM4KYDjASzbAewvgFMGcFIAxwNYtgPYXwCnDOCkAI6XZuDmOll3fkt2HsBeSzPwyvs3irqhUnYewF5LN/Bzsl0twKkCOCmA4wEs2wHsHMCBBHBSAMcDWLYD2DmAAwngpACOB7BsJwVee77s60HNv1v4AGMBnNRIAa+4UrY7Vi3b9QdwUgDHA1i2A9g5gF0C2DmAvQawbAewcwC7BLBzAHsNYNkOYOcAdglg5wD2GsCyHcDOAewSwM4B7DWAZTuAnQPYJYCdA9hrAMt2ADsHsEsAOwew1wCW7QB2DmCXAHYOYK8BLNsB7BzALgHsHMBeA1i2A9g5gF2yHfie+bLPsTr/R7LzAE5Z+MBV78h2n1sh2wGcMoCTAjgewLIdwM4B7BLAzgHsNYBlO4CdA9glgJ0D2GsAy3YAOwewSwA7B7DXAJbtAHYOYJcAdg5g93qP9zrcmgB8m+y9gJWFB2SPDGCXggY+VVM6Oiu7ZHln4h0JwPOEb/GC12U7gF0KGnjxgm2tp9t2LLwl8Q6AZTvbgfOOxF6cmPT3W35dFevTy4bsPlklK+dK2a6wTLYrnyzbfeEc2a5qrHB3zhdku8nlsl1ZoWz3pRuDBZ6xPvZi08y/33K6PVZr15DdiXZZ70h3bUEfKNwdG6G32yYdJv1m6Q+4sfDi6qXVZUVNXo4lWxL8Kbq7vq62rr47/Y+F0pCP58GUCQGsPICVB7DyAFYewMoDWHkAKw9g5QUHPEv4/mBpZRXBnjd/arDnVU4Vfh6stIr7A7MYVHDA0ncXSpN+Ari01muDPc8sagv2vN8I363oLYCHHcD+AjiQAB52APsL4EACeNidacDCj30Tt+qFYM9rrwr2PHNdR7DnPb862PP6Cw74vcBO6u9kT8AHBv0Agz6v52TAB8bib7KUB7DyAFYewMoDWHkAKw9g5QGsvACAm2aOv6n/86F++U+517QEeJ4xzTm+jxt84IIxY8Z8McDzDn9uXMUbvs8bOPCHY6K97P/EgfwDdxf94nBlTfS1PR/Z+da/fT2484zpmZ3t97ghB37spebmvwZ43qcePnqX/7+DHziwtbm5uX76Cd8nDso/8G8/Ycy20uhr/3O5MY9fHtx5xqytCgB44MDTY4L4FLqB83Zd1Gc6dwd4YLTFr/o+cHD+geuqIz/yRke/iEdvT+8bN98b3Hlmz7S9AQAPHLhn/FVT//1gcOf96upbSxcJv+SI6MBIL9/g+7wh+QeuXRr5qZF1PPb641mFx4I7r3f+sy0BAA8c+PJFzzZ/ZXZw560e9bO/fPNfA3yAke/zpQH8nj64YH4Gt2XHf/y1rpwR3Hl1N5oggIc8QPPBKOGXcRKc95PI77+nsn3/sXLwA3xlvt/TEvIPXF9mzI6PR19b94gx7VmevsBAyvOuH5c/ISu/IbgH+OrWyE+Vs/2+G3fgvM0R4K6z24N7gMbc83O/pyUUxJ+iN59ctNyYJw89U/Tnw/fMCu681oMHd4866PcHzKADt47//bvLfP8UGTjvZP7jx++b4/e8QQeavqm+/5CfUADPg3eW5y+JKORs6fteQe4VfwnuvMjrQfwSPejANYXjrj4c4Hm/L8+90v8fsgYduEv6tZ7E8TdZygNYeQArD2DlAaw8gJUHsPIAVh7AygNYeQArD2DlAaw8gJUHsPIAVh7AygNYeQArD2Dl6QKemxVr3Rjnu+8Z7/vD8jMuXcDvd3RcsKWj4+BjznePPxruw7EhXcCRirca0zzNvPnpu/Mve+XS3LuM2T5j4g2xf2DzmrMu+N3cFWXmqQs/uvDY4IUxPbePz3/ANFSY6H/N0dH64uJHiz+8OHrLzauMqbljJL9rw0ot8Fm/aJtVcGBHVltr/v+2f63/y/Dlvd+cd9vuvXn1bUuqBy0i9zx54b4/jtnzIXBktPvcnYcuKzbxi6O3PD3PmPLtI/udG0ZqgSd2m2XfMGbK/kevM+bE2Nhn/kSAc7vM2puMeWd0z8Aics+Gkt2mpetD4Mjo/nuN2Vxs4hdHb3kv5929BUF/9b30pxZ4mjHfWxH53/0rxhYUFOTGfo2OAJcYs2x55NVzjg4sIv/b/cPif364Mwr8SgQ4Mrrpp8a8VmziF0dvMVc8ueb2kfyeDS/9wOuWGNO7vy96XwQ4cvPaJdFPx+0eArzvQN9rl2xomGXMxoro5WbZfcZsKTbxi6O3mB8vmfPiiH7XhpV+4MPnbu1YXhG7rx94T96L7UsWmSHAq2YcemvWuubRu9vn9gM3ntd0dH6xiV8cA943oSAD/41d/cDmN58YO39P7L5+YLOxdNzVbw8FPn5VzoT/7Or7dm75E3HORyaXbvgXE784douZfuuIfa+GnzrggHprlzE7Pzv0ttnPj8xj8RXAzm0/73BX1arBt3ywtej0SD0aHwHs0gPnTb7x/cE3bCrYNFKPxU8AKw9g5QGsPICVB7DyAFYewMoDWHkAKw9g5QGsPICVB7DyAFYewMoDWHl/A2ynusSppmflAAAAAElFTkSuQmCC" alt="histo_2.png"/> </p> </div> <div class="org-src-container"> <pre class="src src-R">nd <span style="color:#008b8b;"><- with(rott2b, data.frame(age=seq(min(age), max(age), length=301), hormon=<span style="color:#8b2252;">"no", pr_1=3.43, time=1))
s <span style="color:#008b8b;"><- predict(fit, newdata=nd, type=<span style="color:#8b2252;">"surv", se.fit=<span style="color:#228b22;">TRUE)
<span style="color:#0000ff;">ci.polygon <span style="color:#008b8b;"><- <span style="color:#a020f0;">function(x, y, ...) polygon(c(x,rev(x)), c(y[,1],rev(y[,2])), ...)
matplot(nd$age, s, type=<span style="color:#8b2252;">"n", xlab=<span style="color:#8b2252;">"Age (years)")
ci.polygon(nd$age, s[,2:3], col=<span style="color:#8b2252;">"grey", border=<span style="color:#8b2252;">"grey")
lines(nd$age, s[,1])
</span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#a020f0;"></span style="color:#008b8b;"></span style="color:#0000ff;"></span style="color:#228b22;"></span style="color:#8b2252;"></span style="color:#008b8b;"></span style="color:#8b2252;"></span style="color:#008b8b;"></pre> </div> <div class="figure"> <p><img 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" alt="surv_1_age.png"/> </p> </div> <div class="org-src-container"> <pre class="src src-R">s <span style="color:#008b8b;"><- predict(fit, newdata=transform(nd,time=5), type=<span style="color:#8b2252;">"surv", se.fit=<span style="color:#228b22;">TRUE)
matplot(nd$age, s, type=<span style="color:#8b2252;">"n", xlab=<span style="color:#8b2252;">"Age (years)")
ci.polygon(nd$age, s[,2:3], col=<span style="color:#8b2252;">"grey", border=<span style="color:#8b2252;">"grey")
lines(nd$age, s[,1])
</span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#8b2252;"></span style="color:#228b22;"></span style="color:#8b2252;"></span style="color:#008b8b;"></pre> </div> <div class="figure"> <p><img src="data:image/png;base64,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" alt="surv_5_age.png"/> </p> </div> </div> </div> </div> <div id="postamble" class="status"> <p class="author">Author: Mark Clements</p> <p class="date">Created: 2018-08-02 Thu 11:29</p> <p class="validation"><a href="http://validator.w3.org/check?uri=referer">Validate</a></p> </div> </body> </html>
