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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。 档案大小:51.7 MB 生物医学研究统计软件，具有丰富的功能，图形类型和一个高级模块进行ROC图分析。MedCalc是为满足生物医学研究者对大数据集的统计分析而设计的。它为进行接收机工作特性曲线分析、数据绘制、Bablok和Deming回归等提供了必要的工具和功能。 通过一个超过100,000行的集成电子表格，MedCalc能够读取和显示从Excel、SPSS、Dbase、Lotus导入的详细数据，或者从SYLK、DIF或文本文件中提取的详细数据。这些信息可以很容易地分类、过滤或编辑。 内置的数据浏览器提供了一个舒适的方式轻松地管理数据,变量,指出,文本和图表,而数组支持的图形和图表(散点图,方法比较图表,图表子组或24连续变量,生存曲线,连续测量,标准化意味着阴谋和更多)使它适合分析趋势和比较信息。 MedCalc最重要的特征之一是其ROC曲线分析能力。它可以生成95%置信界的ROC曲线图，计算特异性、敏感性、所有阈值的预测值、似然比，生成结合体图，确定ROC图下的面积大小。可以比较多达6条ROC曲线，计算面积、标准误差、p值等之间的差异。 MedCalc能够处理丢失的数据，创建子组，计算百分位等级和权力转换。它具有离群值检测、相关和回归工具、Bland和Altman绘图，同时还使您能够运行Anova、方差比、平均值、属性、卡方、Fisher和t检验。 由于使用了多重比较图函数，可以很容易地生成统计报告的摘要，并且可以并排放置和查看数据。 为了最大限度地发挥其潜力，MedCalc至少需要基本的统计学知识。它广泛的特性使其成为运行方法比较研究和分析生物医学数据的必备工具。
File size: 51.7 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. MedCalc is capable of handling missing data, creating subgroups, calculating percentile ranks and power transformation. It features outlier detection, correlation and regression tools, Bland & Altman plotting, while also enabling you to run Anova, variance ratio, mean, propertion, Chi-Square, Fisher and T-tests.
A summary of the statistical report can be easily generated and data can be placed and viewed side-by-side thanks to the multiple comparison graphs function.
MedCalc requires at least basic statistics knowledge in order to get the most out of its potential. Its extensive array of features make it a must-have tool for running method comparison studies and analyzing biomedical data.
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发表于 2020-6-11 17:38:44
