Biomedical subjects

U Grouven

Publications and source records attributed to U Grouven.

22 records · Page 2Linked to original sources

PubMed1992

Application of adjusted survival curves to renal transplant data.

An important means in the analysis of survival time data is the estimation and graphical representation of survival probabilities. In this paper unifactorial parametric and non-parametric survival curve estimators and two types of adjusted survival curves based on a parametric multifactorial approach are applied to renal transplant data. It is shown that the resulting survival curves can differ substantially. The unifactorial survival curves yield biased results in case of serious disequilibrium in the data. This drawback of the unifactorial methods has been overcome by the use of adjusted survival curves which take possible distortions in the data set into account. The benefits of adjusted survival curves in assessing potentially prognostic factors are elucidated by the application to data from renal transplantation.

Humans↗

PubMedDate not supplied

Improved methods of estimating survival probabilities applied to renal transplant data.

In the evaluation of clinical studies of different kinds with survival time as the response variable to be analysed the estimation of survival probabilities plays an important role. The ordinary procedure in survival data analysis for estimating survival probabilities is the Kaplan-Meier product-limit estimator. However, in the case of heavy censoring or if the largest observed failure times are censored the product-limit method is known to be a biased estimator of the survival function. Recently, two improved methods of estimating survival functions, a semiparametric procedure and an approach using splines, were proposed (Klein JP, Lee SC and Moeschberger ML, Biometrics, 46 (1990) 795-811; Whittemore AS and Keller JB, Biometrics, 42 (1986) 495-506). These new methods are less biased than the product-limit estimator, especially for heavily censored data. A computer program based on the integrated statistical and graphical software package RS/1 was developed for the calculation and graphical representation of the new estimators. Their improved properties are illustrated by the application to renal transplant data.

Computer Graphics↗

PubMedDate not supplied

Automatic classification algorithms of the EEG monitor Narcotrend for routinely recorded EEG data from general anaesthesia: a validation study.

Impacts of hypnotic drugs on brain function are reflected in the EEG. The EEG monitor Narcotrend performs an automatic classification of the EEG using a scale which was proposed by Kugler for visual evaluation of the EEG. In this article the results of a validation study of the automatic classification algorithms implemented in the EEG monitor Narcotrend are presented. Visual and automatic classification of EEG data recorded in routine clinical practice were compared. The correlation between visual and automatic assessment was high (Spearman rank correlation r = 0.90, prediction probability Pk = 0.90) and a sufficient agreement between visual and automatic assessment was achieved for 92% of the analysed EEG epochs. The results of the study suggest that the automatic classification algorithms implemented in the EEG monitor Narcotrend yield a reliable assessment of the depth of hypnosis.

Algorithms↗

PubMedDate not supplied

Ordinal logistic regression in medical research.

Medical research workers are making increasing use of logistic regression analysis for binary and ordinal data. The purpose of this paper is to give a non-technical introduction to logistic regression models for ordinal response variables. We address issues such as the global concept and interpretation of logistic models, the model building procedure from a practical point of view, and the assessment of the model adequacy. For illustrative purposes we apply these methods to real data of a study investigating the association between glycosylated haemoglobin and retinopathy. We give some recommendations for the use and assessment of ordinal logistic regression models in medical research.

Analysis of Variance↗