August 2015
Intermediate to advanced
272 pages
5h 46m
Japanese
Content preview from Think Stats 第2版 ―プログラマのための統計入門
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193
13
章
生存分析
†
生存分析（
Survival analysis
）は、ものごとがどれだけ続くかを記述する方法です。
人間の生存期間の研究によく使われますが、機械部品や電子部品の「生存」、あるい
はもっと一般的に出来事が起こるまでの時間の期間に適用されます。
知り合いが「生死に関わる」病気に罹ったことがあるなら、診断後
5
年間の生存率
である「
5
年生存率」を知っているでしょう。この推定や関連した統計量は、生存分
析の結果です。
13.1
生存曲線
生存分析の基本概念は、生存曲線（
survival curve
）、
S(t)
です
‡
。これは、期間
t
に
t
より長く生存する確率を対応させる関数です。期間あるいは「生存時間」の分布が
わかっているなら、生存曲線を見出すのは容易でしょう。
CDF
の補数になります。
S(t) = 1
−
CDF(t)
ここで、
CDF(t)
は、生存時間が
t
以下の確率を示します。
例えば、
NSFG
データセットには、
11,189
の妊娠期間データがあります。このデー
タを読み込んで
CDF
を計算できます。
preg = nsfg.ReadFemPreg()
complete = preg.query('outcome in [1, 3, 4]').prglngth
cdf = thinkstats2.Cdf(complete, label='cdf')
†
本章のコードは、
survival.py
にある。コードのダウンロードや扱い方については、
viii
ページの 「コード
を使う」を参照してほしい。
‡
訳注：本書では、生存曲線と生存関数（ ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.