๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

TUTORIAL IN BIOSTATISTICS SURVIVAL ANALYSIS IN OBSERVATIONAL STUDIES

โœ Scribed by KATE BULL; DAVID J. SPIEGELHALTER

Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
321 KB
Volume
16
Category
Article
ISSN
0277-6715

No coin nor oath required. For personal study only.

โœฆ Synopsis

Multi-centre databases are making an increasing contribution to medical understanding. While the statistical handling of randomized experimental studies is well documented in the medical literature, the analysis of observational studies requires the addressing of additional important issues relating to the timing of entry to the study and the effect of potential explanatory variables not introduced until after that time. A series of analyses is illustrated on a small data set. The influence of single and multiple explanatory variables on the outcome after a fixed time interval and on survival time until a specific event are examined. The analysis of the effect on survival of factors that only come into play during follow-up is then considered. The aim of each analysis, the choice of data used, the essentials of the methodology, the interpretation of the results and the limitations and underlying assumptions are discussed. It is emphasized that, in contrast to randomized studies, the basis for selection and timing of interventions in observational studies is not precisely specified so that attribution of a survival effect to an intervention must be tentative. A glossary of terms is provided.

๐Ÿ“œ SIMILAR VOLUMES

TUTORIAL IN BIOSTATISTICS: BAYESIAN DATA
TUTORIAL IN BIOSTATISTICS: BAYESIAN DATA MONITORING IN CLINICAL TRIALS
โœ PETER M. FAYERS; DEBORAH ASHBY; MAHESH K. B. PARMAR ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 293 KB ๐Ÿ‘ 2 views

Many clinical trials organizations use regular interim analyses to monitor the accruing results in large clinical trials. In disease areas such as cancer, where survival is usually a major outcome variable, ethical considerations may lead to a stipulated requirement for data monitoring of mortality.

Tutorial in Biostatistics. Meta-analysis
Tutorial in Biostatistics. Meta-analysis: formulating, evaluating, combining, and reporting by S-L. Normand, Statistics in Medicine, 18, 321โ€“359 (1999)
โœ Theo Stijnen ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 77 KB

Figure 1. Listing of SAS data used in the example. STYID identi"es the di!erent studies involved in the meta-analysis. The variable DIFF is the estimated treatment e!ect (mean stay (days) in hospital in treatment group minus control group), and VDIFF is the corresponding squared standard error 10. G

Tutorial in Biostatistics. Meta-analysis
Tutorial in Biostatistics. Meta-analysis: formulating, evaluating, combining, and reporting by S-L. T. Normand, Statistics in Medicine, 18, 321โ€“359 (1999)
โœ John B. Carlin ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 113 KB

Meta-analysis is an area of modern biostatistics where statisticians are in some danger of falling behind the galloping onrush of applications and even newly proposed statistical methods (some as yet unevaluated) that appear in medical and epidemiological journals. Normand's tutorial is therefore ve