Causal Inference for Statistics, Social, and Biomedical Scie

Causal Inference for Statistics, Social, and Biomedical Scie - Guido W Imbens

Causal Inference for Statistics, Social, and Biomedical Scie


Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including, matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.
Citeste mai mult

-20%

transport gratuit

PRP: 579.61 Lei

!

Acesta este Pretul Recomandat de Producator. Pretul de vanzare al produsului este afisat mai jos.

463.69Lei

463.69Lei

579.61 Lei

Primesti 463 puncte

Important icon msg

Primesti puncte de fidelitate dupa fiecare comanda! 100 puncte de fidelitate reprezinta 1 leu. Foloseste-le la viitoarele achizitii!

Livrare in 2-4 saptamani

Descrierea produsului


Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including, matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.
Citeste mai mult

De pe acelasi raft

Parerea ta e inspiratie pentru comunitatea Libris!

Acum se comanda

Noi suntem despre carti, si la fel este si

Newsletter-ul nostru.

Aboneaza-te la vestile literare si primesti un cupon de -10% pentru viitoarea ta comanda!

*Reducerea aplicata prin cupon nu se cumuleaza, ci se aplica reducerea cea mai mare.

Ma abonez image one
Ma abonez image one