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Rank correlation

Description

Calculates Spearman's rho and/or Kendall's tau rank correlation coefficients.

When the distribution of variables is not Normal, the degree of association between the variables can be calculated using Rank correlation. Instead of using the precise values of the variables, the data are ranked in order of size, and calculations are based on the ranks of corresponding values X and Y. The program will calculate Spearman correlation coefficient rho and/or Kendall's tau with P-value, and a 95% confidence interval (CI) for the correlation coefficient, i.e. the range of values which contains the true correlation coefficient with 95% probability.

Required input

  • Variable Y - Variable X: select the 2 variables of interest.
  • Filter: (optionally) enter a data filter in order to include only a selected subgroup of cases in the statistical analysis.
  • Correlation coefficients: select Spearman's rho and/or Kendall's tau.

    The confidence interval for Kendall's tau is estimated using the bias-corrected and accelerated (BCa) bootstrap (Efron, 1987; Efron & Tibshirani, 1993). Click the Advanced... button for bootstrapping options such as number of replications and random-number seed.
  • Graph options
    • Scatter diagram: show a scatter diagram.
    • Draw line of equality: option to draw the line of equality (y=x) line in the graph.
    • Heat map: option to display a heatmap, where background color coding indicates density of points, suggesting clusters of observations.

Results

  • Sample size: the number of (selected) data pairs
  • The Spearman's rho and/or Kendall's tau correlation coefficients with P-value and 95% Confidence Interval, i.e. the range of values which contains the true correlation coefficient with probability 95%.

Literature

  • Altman DG (1991) Practical statistics for medical research. London: Chapman & Hall.
  • Armitage P, Berry G, Matthews JNS (2002) Statistical methods in medical research. 4th ed. Blackwell Science.
  • Bland M (2000) An introduction to medical statistics, 3rd ed. Oxford: Oxford University Press.
  • Efron B (1987) Better Bootstrap Confidence Intervals. Journal of the American Statistical Association 82:171-185.
  • Efron B, Tibshirani RJ (1993) An introduction to the Bootstrap. Chapman & Hall/CRC.

See also

Link

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