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Results for “Morbidity--statistics”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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At least 91 records · Page 5Linked to original sources
PubMed1979

General right censoring and its impact on the analysis of survival data.

This paper concerns general right censoring and some of the difficulties it creates in the analysis of survival data. A general formulation of censored-survival processes leads to the partition of all models into those based on noninformative and informative censoring. Nearly all statistical methods for censored data assume that censoring is noninformative. Topics considered within this class include: the relationships between three models for noninformative censoring, the use of likelihood methods for inferences about the distribution of survival time, the effects of censoring on the K-sample problem, and the effects of censoring on model testing. Also considered are several topics which relate to informative censoring models. These include: problems of nonidentifiability that can be encountered when attempting to assess a set of data for the type of censoring in effect, the consequences of falsely assuming that censoring is noninformative, and classes of informative censoring models.

Clinical Trials as Topic↗
PubMed1979

Detecting systematic errors in multi-clinic observational data.

In multi-clinic studies it is hard to maintain a uniformly high quality of measurement and coding. Systematic errors almost always occur, in spite of the best of intentions and the most rigid protocols. It is the statistician's responsibility to plan for the detection of these errors, as well as to try to avoid them and not be misled by them. The practice of examining the univariate and multivariate sample frequency distributions of the variables under study, with an eye open for anything that looks puzzling, can be very helpful in detecting and trying to correct systematic errors that would bias the analysis. Examples are given from a 21-clinic study on pregnancy and child development.

Humans↗