Warning: Undefined variable $zfal in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 525
Deprecated: str_replace(): Passing null to parameter #3 ($subject) of type array|string is deprecated in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 525
Warning: Undefined variable $sterm in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 530
Warning: Undefined variable $sterm in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 531
English Wikipedia
Nephropedia Template TP (
Twit Text
DeepDyve Pubget Overpricing |
lüll Statistics in review Part 2: generalised linear models, time-to-event and time-series analysis, evidence synthesis and clinical trials Moran JL; Solomon PJCrit Care Resusc 2007[Jun]; 9 (2): 187-97In Part I, we reviewed graphical display and data summary, followed by a consideration of linear regression models. Generalised linear models, structured in terms of an exponential response distribution and link function, are now introduced, subsuming logistic and Poisson regression. Time-to-event ("survival") analysis is developed from basic principles of hazard rate, and survival, cumulative distribution and density functions. Semi-parametric (Cox) and parametric (accelerated failure time) regression models are contrasted. Time-series analysis is explicated in terms of trend, seasonal, and other cyclical and irregular components, and further illustrated by development of a classical Box-Jenkins ARMA (autoregressive moving average) model for monthly ICU-patient hospital mortality rates recorded over 11 years. Multilevel (random-effects) models and principles of meta-analysis are outlined, and the review concludes with a brief consideration of important statistical aspects of clinical trials: sample size determination, interim analysis and "early stopping".|*Hospital Mortality[MESH]|*Linear Models[MESH]|*Survival Analysis[MESH]|Clinical Trials as Topic/*statistics & numerical data[MESH]|Humans[MESH]|Sample Size[MESH] |