PACKAGE | |STAT Data Manipulation and Analysis, by Gary Perlman |
---|---|
NAME | rankrel - rank order statistics for related samples |
SYNOPSIS | rankrel [-ry] [-c maxcases] [names] |
WEB FORM | rankrel can be run from an online web form. |
DESCRIPTION |
rankrel analyses data from ordinally ranked data obtained from
related/matched samples. The input consists of scores from several
samples, conditions, or groups. Each condition's data are in a
separate column. The scores need not be ranks; they will be ranked by
the program. For each condition, the number of scores, extrema and
quartiles are reported. Conditions are compared for equality of
location using the sign test, the Wilcoxon signed-ranks test, and the
Friedman two-way analysis of variance of ranks. A matrix of Spearman
rank-order correlation coefficients (rho) is printed.
The sign test and the Wilcoxon test are only used when there are two conditions. When there are fewer than 25 paired cases that are different, the exact binomial probability is computed; for larger N, the normal approximation is used.
Probability of Obtained Statistics
|
OPTIONS |
The following standard help options are supported. The program exits after displaying the help.
|
EXAMPLE |
The following data are from Siegel, page 79. The command names the
conditions "school" and "home."
> rankrel school home 82 63 69 42 73 74 43 37 58 51 56 43 76 80 65 62 sign test: 0.144531 (one-tailed) Wilcoxon T = 4, N = 8 p approximated with z: .026892 (one-tailed) tabled critical value for T for one-tailed p = .025: 4 Friedman R = 2 Spearman Rank Correlation (rho) = .786 |
LIMITS | Use the -L option to determine the program limits. |
MISSING VALUES | Cases with missing data values (NA) are counted but not included in the analysis. |
SEE ALSO |
pair,
regress, and anova perform the normal-theory parametric
counterparts to this non-parametric, distribution-free analysis.
To see a scatterplot of ranks, the ranksort filter can be used as a pre-processor for the pair plotting option. rankind analyses ordinal data for independent conditions. Siegel, S. (1956) Nonparametric Statistics for the Behavioral Sciences. New York: McGraw-Hill. |
WARNING | When the program advises to check a table for exact probabilities of significance tests, it may still compute approximate values. These approximations should not be used for serious work. |
UPDATED | January 20, 1987 |