MedCalc is a statistical software package for the biomedical sciences. It has an integrated spreadsheet which can be configured to contain up to 676 columns and 100000 rows. The program correctly handles missing data and provides reliable date arithmetic. MedCalc can import Excel, SPSS, DBase and Lotus files, and files in SYLK, DIF or text format. Comprehensive on line help is available and, in addition to a manual in PDF format, a complete user manual is available on the web. Special features of the program are, amongst others, lots of graphs including Kaplan-Meier survival plots, Bland & Altman plot, Deming and Passing & Bablok regression for method comparison. MedCalc also includes a complete module for Receiver Operating Characteristic (ROC) curve analysis, with calculation of sensitivity, specificity, likelihood ratios, and positive and negative predictive values for all possible threshold values. The program calculates the area under the curve (AUC) with its standard error and 95% confidence interval. Furthermore, threshold values can be selected in an interactive dot diagram with automatic calculation of corresponding sensitivity and specificity. Comparison of ROC curves includes calculation of the difference between the areas under the curves, with standard error, 95% confidence interval and P-value. Works with Windows versions 98SE and later. Certified for Windows Vista. Data management Integrated spreadsheet 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 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, see Graph gallery. Data point identification in graphs. Draw text boxes, lines, arrows and connectors. 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 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 Sampling: calculation of sample sizes
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