Multivariable Analysis: An IntroductionYale University Press, 1996 M01 1 - 613 páginas For physicians, nurses, and all others who confront increasingly complex statistical methods in research, Dr. Alvan R. Feinstein offers welcome help. He has written a highly readable explanation of the uses and significance of multivariable analysis in medical and life science research. A physician with wide experience in both clinical work and research, Dr. Feinstein succeeds in demystifying arcane vocabulary and unfamiliar mathematics. His book is a roadmap taking the reader from the basics of univariate and bivariate statistics, through methods of converting information into data coded for computers, and on to multivariable statistics. Dr. Feinstein focuses on four methods common in the medical literature: multiple linear regression, multiple logistic regression, discriminant function analysis, and Cox regression. He also discusses such new methods as recursive partitioning and conjunctive consolidation. Clarifying examples and illustrations abound, and an accompanying floppy disk helps to facilitate learning. |
Contenido
Preparing for Multivariable Analysis | 83 |
Basic Strategies of Targeted Algebraic Methods | 205 |
Multivariable explorations and reductions | 227 |
Evaluations and illustrations of multiple linear regression | 264 |
Regression for Nondimensional Targets | 295 |
Evaluations and illustrations of logistic regression | 331 |
Proportional hazards analysis Cox regression | 370 |
Evaluations and illustrations of Cox regression | 398 |
TargetedCluster Methods | 475 |
Multicategorical stratification | 507 |
Recursive partitioning | 529 |
Additional discussion and conclusions | 559 |
Otras ediciones - Ver todas
Multivariable Analysis: A Practical Guide for Clinicians Mitchell H. Katz Vista previa limitada - 2006 |
Términos y frases comunes
algebraic model anatomic stage b₁ b₂ baseline basic binary variables BMDP program box plot calculated cancer Chapter checked chi-square cited clinical clusters coding corresponding covariates Cox regression decisions degrees of freedom dimensional discussed in Section effect error estimates example expressed formula full regression Gaussian goal gradient group variance hazard function hazard ratio hematocrit illustrative data set impact incremental independent variables interaction interval linear regression log likelihood logistic regression mathematical matrix metastasis multiple linear regression multivariable analysis odds ratios ordinal variables P-VALUE partitioning patients pattern PCTWTLOS polytomous predictive printout problem procedure produce prognostic quantitative recursive partitioning regression coefficients regression diagnostics residual score sequential shown in Fig shows standardized standardized coefficients statistical step stepwise stepwise regression stochastically significant strata strategy survival analysis survival rates SXSTAGE symptom stage Table target variable tion TNM stage univariate X₁ Y₁ zones
Pasajes populares
Página 592 - MB et al.: The American College of Rheumatology, 1990 Criteria for the Classification of Fibromyalgia. Report of the Multicenter Criteria Committee.
Página 589 - Gail MH, Brinton LA, Byar DP, et aL Projecting individualized probabilities of developing breast cancer for white females who are being examined annually.
Página 592 - L. Stratification of morbidity and mortality outcome by preoperative risk factors in coronary artery bypass patients: a clinical severity score.
Referencias a este libro
Breast Cancer: Translational Therapeutic Strategies Gary H. Lyman,Harold J. Burstein Sin vista previa disponible - 2007 |