Factors potentially related to these outcomes were assessed using multiple logistic regression analyses. The software is routinely applied in several clinical study groups. Results On the basis of a working example, we demonstrate how to use KMWin and present its main functions. Conclusions We conclude that our tool is well suited and convenient for repetitive analyses of survival time data. Two violations of the iliac cortex were noted, with an average breach distance of 7. We show how to control the interface, customize the graphical output, and analyse survival time data.

Gross, Arnd; Ziepert, Marita; Scholz, Markus Background Analysis of clinical studies often necessitates multiple graphical representations of the results.

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Many professional software packages are available for this purpose. Most packages are either only commercially available or hard to use especially if one aims to generate or Liikme Size Hedgehog a huge number of similar graphical outputs.

The clinical relevance of such changes is controversial.

KMWin is based on the statistical software environment R and provides an easy to use graphical interface. Survival time data can be supplied as SPSS savSAS export xpt or text file datwhich is also a common export format of other applications such as Excel.

Figures can directly be exported in any graphical file format supported by R. Results On the basis of a working example, we demonstrate how to use KMWin and present its main functions. We show how to control the interface, customize the graphical output, and Liikme Size Hedgehog survival time data.

A number of comparisons are performed between KMWin and SPSS regarding graphical output, statistical output, data management and development. Although the general functionality of SPSS is larger, KMWin comprises a number of features useful for survival time analysis in clinical trials and other applications.

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These are for example number of cases and number of cases under risk within the figure or provision of a queue system for repetitive analyses of updated data sets.

Moreover, major adjustments of graphical settings can be performed easily on a single window.

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Conclusions We conclude that our tool is well suited and convenient for repetitive analyses of survival time data. It can be used by non-statisticians and provides often used functions as well as functions which are not supplied by standard software packages.

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The software is routinely applied in several clinical study groups. Survival time data can be supplied as SPSS sav, SAS export xpt or text file dat, which is also a common export format of other applications such as Excel.

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