Data were analyzed with a multivariate logistic regression for predictors of operative mortality, Kaplan-Meier estimates of survival, and a Cox multivariate ... SJ Melby,A Zierer,SP Kaiser,... - 《Annals of Thoracic Surgery》 被引量: 503发表: 2007年 SAS System for Regression, 3rd Edition Fe...
Univariate and multivariate Cox regression was performed to analyze potential modifiers of implant success. Results The overall implant success rate was 96.7%. The statistically significant modifiers of success on multivariate analysis (P<0.05) were duration of functional use (P<0.001), type of ...
Cox D: Analysis of Binhry Data, Methuen and Co., London, 1970. Cox D: Regression models and life-tables, J R Stat Sot Ser. 34 (1972) 187-220. Neyman J: First Course in Probability and Stafistics, Henry Holt, New York, 1950. Puska P, Salonen J, Nissinen A, Tuomilehto J, ...
CSS was poor when associated with a KI67 cut-off point >14% (p=0.013, HR 14.85; CI 1.074-120.53) (Cox regression model). Disease-free survival (DFS) was not associated with Ki67 CONCLUSIONS: Prognosis of luminal breast carcinoma can be predicted using Ki67 as a continuous variable and a...
In multivariate analyses using a Cox's proportional-hazards regression model with 9 variables, nm23-H1 showed the fourth greatest contribution to patient ... Y Tokunaga,T Urano,K Furukawa,... - 《International Journal of Cancer》 被引量: 190发表: 2010年 Polo-like kinase isoform expression is...
Path estimates are standardized regression coefficients, so they must be squared to obtain the proportion of variance accounted for in the dependent variable. E represents unique environmental effects. The subscripts C and S represent common factor and disorder-specific effects, respectively. The first,...
where LL is the logarithm of the model likelihood (log-likelihood),cis the number ofcovariatesandsthe number of ancillary parameters (e.g. 2 in the case of the Weibull;λands). Alowervalue of the AIC suggests a better model. Note, however, that the likelihood computed in a Cox model is...
for example using linear mixed models and Cox regression models, can lead to biased effect size estimates [1]. The same criticism has also been levelled at the application of so-called two-stage models [2]. The motivation for using joint models can be broadly separated into interest in draw...
A Cox proportional hazards model was used to evaluate the effect of the mentioned variables on OS. All analyses were done using SAS System® version 9.2. Results: Of 240 patients enrolled, pre-AZA SF levels were available for 190 patients. The median pre-treatment SF level was 1001 ng/mL...
It has been repeatedly shown elsewhere that if the longitudinal and event-time outcomes are correlated, then modelling the two outcome processes separately, for example using linear mixed models and Cox regression models, can lead to biased effect size estimates [1]. The same criticism has also ...