Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (2012) (快遞進口) (2ND ed.)

This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes.

Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way.

The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.

這本新書提供了一個統一、深入且易讀的介紹，涵蓋了生物統計學中最廣泛使用的多預測變數迴歸方法：連續結果的線性模型、二元結果的邏輯模型、右設限生存時間的Cox模型、長期和階層結果的重複測量模型，以及計數和其他結果的廣義線性模型。

將這些主題一起處理，可以充分利用它們之間的共同點。作者指出了他們所介紹的每個模型在選擇、估計、檢查和解釋方面的許多共同元素。他們還表明，這些迴歸方法在處理混淆、中介和因果效應交互作用方面基本上是相同的。

這本書使用Stata進行分析的例子來自生物醫學背景，但也可以推廣到其他應用領域。雖然假設讀者已經有一門統計學的基礎課程，但書中還包括一章對基本統計方法的回顧。書中涵蓋了一些高級主題，但呈現方式仍然直觀。此外，還提供了關於複雜調查回歸分析的簡要介紹和進一步閱讀的註解。