44,95 €
44,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
22 °P sammeln
44,95 €
44,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
22 °P sammeln
Als Download kaufen
44,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
22 °P sammeln
Jetzt verschenken
44,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
22 °P sammeln
  • Format: PDF

This book presents a wide variety of statistical approaches for analyzing pharmacoepidemiologic data. It covers both commonly used techniques, such as proportional reporting ratios for the analysis of spontaneous adverse event reports, and newer approaches, such as the use of marginal structural models for controlling dynamic selection bias in the analysis of large-scale longitudinal observational data. Many real examples from both mental and physical health disorders illustrate the use of the methods.

Produktbeschreibung
This book presents a wide variety of statistical approaches for analyzing pharmacoepidemiologic data. It covers both commonly used techniques, such as proportional reporting ratios for the analysis of spontaneous adverse event reports, and newer approaches, such as the use of marginal structural models for controlling dynamic selection bias in the analysis of large-scale longitudinal observational data. Many real examples from both mental and physical health disorders illustrate the use of the methods.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Robert D. Gibbons, PhD, is a professor of biostatistics in the Departments of Medicine, Public Health Sciences, and Psychiatry and director of the Center for Health Statistics at the University of Chicago. He is a fellow of the American Statistical Association (ASA) and a member of the Institute of Medicine of the National Academy of Sciences. He has been a recipient of the ASA's Outstanding Statistical Application Award and two Youden Prizes.

Anup Amatya, PhD, is an assistant professor in the Department of Public Health Sciences at New Mexico State University. His current research focuses on meta-analysis of sparse binary data and sample size determination in hierarchical non-linear models.