医学计算器MedCalc 20.1.0 Multilingual

MedCalc 是一个专门为医学工作者设计的医学计算器，功能齐全。它可以帮助医生快速作出普通的医学计算，从而对症下药。提供超过76种常用的规则和方法，包括：病人数据、单位参数、费用计算等等。

用于生物医学研究的统计软件，具有丰富的功能、图形类型和用于执行 ROC 图形分析的高级模块。MedCalc 旨在满足生物医学研究人员对大型数据集进行统计分析的要求。它为执行接收器操作特征曲线分析、数据绘图、Bablok 和 Deming 回归等提供了必要的工具和功能。

MedCalc 具有超过 100,000 行的集成电子表格，能够读取和显示从 Excel、SPSS、Dbase、Lotus 导入或从 SYLK、DIF 或文本文件中提取的详细数据。可以轻松地对信息进行分类、过滤或编辑。

内置数据浏览器提供了一种轻松管理数据、变量、注释、文本和图表的舒适方式，而支持的图表和图表阵列（散点图、方法比较图、子组图表或多达 24 个连续变量，生存曲线、连续测量、标准化平均图等）使其非常适合分析趋势和比较信息。

MedCalc 最重要的功能之一与其 ROC 曲线分析功能有关。它可以生成具有 95% 置信区间的 ROC 曲线图，计算所有阈值的特异性、灵敏度、预测值、似然比，生成结论性图并确定 ROC 图下区域的大小。最多可以比较 6 条 ROC 曲线，计算区域之间的差异、标准误差、P 值等等……

File size: 68.8 MB
Statistical software for biomedical research with a rich set of functions, graph types and an advanced module for performing ROC graph analysis. MedCalc is designed to meet the requirements of biomedical researchers with respect to the statistical analysis of large datasets. It provides the necessary tools and features for performing Receiver Operating Characteristic curve analysis, data plotting, Bablok and Deming regression and more.

With an integrated spreadsheet with over 100,000 rows, MedCalc is capable of reading and displaying detailed data imported from Excel, SPSS, Dbase, Lotus or extracted from SYLK, DIF or text files. The information can be easily sorted, filtered or edited.

The built-in data browser offers a comfortable means of easily managing data, variables, notes, texts and graphs, while the array of supported graphs and diagrams (scatter plots, method comparison graphs, graphs for subgroups or for up to 24 continuous variables, survival curves, serial measurement, standardized mean plots and many more) make it perfect for analyzing trends and comparing information.

One of the most important features of MedCalc is related to its ROC curve analysis capabilities. It can generate the ROC curve graph with 95% confidence bounds, calculate specificity, sensitivity, predictive values for all the thresholds, likelihood ratios, generate conclusive plots and determine the size of an area under the ROC graph. Up to 6 ROC curves can be compared, calculating the differences between the areas, the standard errors, P-values and more…..

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