MedCalc 22
醫學統計師
easy-to-use statistical software
軟體代號:884
瀏覽次數:1619
多人版
教育版
商業版
再啟動服務
試用版
遠端展示
在地教學
遠端安裝啟動服務
原廠技術服務
教育訓練
教學範例檔
中文安裝手冊
永久授權
中文型錄
英文型錄
安裝序號
合法保證
原廠手冊
電子英文手冊
64 Bit
ESD網路下載
授權下載光碟
影音教學檔
Features
Data management
- Integrated spreadsheet (pop-up) with 16384 columns and up to 100000 rows.
- Correct handling of missing data.
- Outliers can easily be excluded.
- Built-in WYSIWYG text editor.
- Imports Excel, Excel 2007, SPSS, DBase and Lotus files, and files in SYLK, DIF or plain text format.
- Easy selection of subgroups for statistical analysis.
Documentation
- Comprehensive help file.
- Manual in PDF format (go to download area).
- Complete HTML manual on MedCalc web site.
- Context help in dialog boxes.
ROC curve analysis
- Area under the curve (AUC) with standard error, 95% confidence interval, P-value. Offers choice between methodology of DeLong et al. (1988) and Hanley & McNeil (1982 1983).
- List of sensitivity, specificity, likelihood ratios, and positive and negative predictive values for all possible threshold values.
- ROC curve graph with 95% Confidence Bounds.
- Threshold values can be selected in an interactive dot diagram with automatic calculation of corresponding sensitivity and specificity.
- Plot of sensitivity and specificity versus criterion values.
- Interval likelihood ratios.
- Comparison of up to 6 ROC curves: difference between the areas under the ROC curves, with standard error, 95% confidence interval and P-value.
- Sample size calculation for area under ROC curve and comparison of ROC curves.
- Go to the ROC curve analysis section of the MedCalc manual for more information on ROC curve analysis in MedCalc.
Graphs
- Lots of graphs.
- Data point identification in graphs.
- Name, save and recall graphs and statistics.
- Statistical info in graph windows.
Statistical features
- Summary statistics, including averages, standard deviation, median, percentiles, etc.
- Tests for Normal distribution: chi-square test, Kolmogorov-Smirnov test, D'Agostino-Pearson test
- Outlier detection
- Histogram and cumulative frequency graphs with option of superimposed plot of the Normal distribution
- Normal plot
- Dot plot
- Box-and-whisker plot
- Correlation, rank correlation (Spearman's rho and Kendall's tau), and scatter diagram
- Simple regression and scatter diagram with choice of 5 different equations for approximating curve (including parabola), residuals plot
- Stepwise multiple regression
- Stepwise logistic regression
- One sample t-test, independent samples t-test (incl. correction for unequal variances - Welch test) and paired samples tests
- Rank sum tests: signed rank sum test (one sample), Mann-Whitney test (independent samples), Wilcoxon test (paired samples)
- Variance ratio test (F-test)
- One-way analysis of variance (ANOVA) with Levene's Test for Unequal Variances, and Student-Newman-Keuls (SNK) test for pairwise comparison of subgroups
- Two-way analysis of variance and post-hoc multiple comparisons
- Analysis of covariance (ANCOVA) and post-hoc multiple comparisons
- Repeated measures analysis of variance
- Kruskal-Wallis test and post-hoc multiple comparisons
- Friedman test and post-hoc multiple comparisons
- Frequencies table, crosstabulation analysis, Chi-square test, Chi-square test for trend (Cochran-Armitage test)
- Tests on 2x2 tables: Fisher's exact test, McNemar test
- Cochran's Q test and post-hoc multiple comparisons
- Frequencies bar charts
- Kaplan-Meier survival curve, logrank test for comparison of survival curves, hazard ratio, logrank test for trend
- Cox proportional-hazards regression
- Meta-analysis: odds ratio (random effects or fixed effects model - Mantel-Heinszel method); summary effects for continuous outcomes; Forest plot
- Reference interval (normal range) (CLSI C28-A3)
- Analysis of Serial measurements with group comparison
- Bland & Altman plot for method comparison (bias plot) - repeatability
- Mountain plot
- Deming regression (method comparison)
- Passing & Bablok regression (method comparison)
- Inter-rater agreement: Kappa and Weighted Kappa
- Intraclass correlation coefficient
- Concordance correlation coefficient
- Cronbach's Alpha
- Responsiveness
- Receiver Operating Characteristics (ROC) curve analysis, sensitivity and specificity (with 95% confidence interval), likelihood ratios, predictive values. Methods of DeLong et al. (1988) and Hanley & McNeil (1982, 1983).
- Interval likelihood ratios
- Comparison of up to 6 ROC curves (with pairwise comparison of the area under the ROC curves, with 95% confidence interval and P-value)
- Interactive dot diagram for selection of threshold values
- Significance of difference between means, percentages and between correlation coefficients
- 95% Confidence Interval for a rate, comparison of rates
- Different data comparison graphs, lines, bars, error bars (1 SD, 2 SD, 1 SEM, 95% CI, percentile ranges, etc.)
- Multiple box-and-whisker plots
- Notched box-and-whisker plots for pairwise comparison of medians
- Dot and line diagram (ladder plot)
- Quality control chart
- Youden plot
- Comparison of proportions
- Odds ratio, relative risk, number needed to treat (NNT)
- Sampling: calculation of sample sizes