help ranksum, help median dialogs: ranksum median
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Title
[R] ranksum -- Equality tests on unmatched data
Syntax
Wilcoxon rank-sum test
ranksum varname [if] [in], by(groupvar) [porder]
Nonparametric equality-of-medians test
median varname [if] [in] [weight], by(groupvar) [median_options]
ranksum options description
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Main
* by(groupvar) grouping variable
porder probability that variable for first group is
larger than variable for second group
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median_options description
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Main
* by(groupvar) grouping variable
exact performs Fisher's exact test
medianties(below) assign values equal to the median to below group
medianties(above) assign values equal to the median to above group
medianties(drop) drop values equal to the median from the analysis
medianties(split) split values equal to the median equally between
the two groups
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* by(groupvar) is required.
by is allowed with the above commands; see [D] by.
fweights are allowed with median; see weight.
Menu
ranksum
Statistics > Nonparametric analysis > Tests of hypotheses > Wilcoxon
rank-sum test
median
Statistics > Nonparametric analysis > Tests of hypotheses > K-sample
equality-of-medians test
Description
ranksum tests the hypothesis that two independent samples (i.e.,
unmatched data) are from populations with the same distribution by using
the Wilcoxon rank-sum test, which is also known as the Mann-Whitney
two-sample statistic (Wilcoxon 1945; Mann and Whitney 1947).
median performs a nonparametric K-sample test on the equality of medians.
It tests the null hypothesis that the K samples were drawn from
populations with the same median. For two samples, the chi-squared test
statistic is computed both with and without a continuity correction.
ranksum and median are for use with unmatched data. For equality tests
on matched data, see [R] signrank.
Options for ranksum
+------+
----+ Main +-------------------------------------------------------------
by(groupvar) is required. It specifies the name of the grouping
variable.
porder displays an estimate of the probability that a random draw from
the first population is larger than a random draw from the second
population.
Options for median
+------+
----+ Main +-------------------------------------------------------------
by(groupvar) is required. It specifies the name of the grouping
variable.
exact displays the significance calculated by Fisher's exact test. For
two samples, both one- and two-sided probabilities are displayed.
medianties(below|above|drop|split) specifies how values equal to the
overall median are to be handled. The median test computes the
median for varname by using all observations and then divides the
observations into those falling above the median and those falling
below the median. When values for an observation are equal to the
sample median, they can be dropped from the analysis by specifying
medianties(drop); added to the group above or below the median by
specifying medianties(above) or medianties(below), respectively; or
if there is more than 1 observation with values equal to the median,
they can be equally divided into the two groups by specifying
medianties(split). If this option is not specified,
medianties(below) is assumed.
Examples
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Setup
. webuse fuel2
Perform rank-sum test on mpg by using the two groups defined by treat
. ranksum mpg, by(treat)
Same as above, but include estimate of probability that the value of mpg
for an observation with treat = 0 is greater than the value of mpg for an
observation with treat = 1
. ranksum mpg, by(treat) porder
Perform Pearson chi-squared test of the equality of the medians of mpg
between the two groups defined by treat
. median mpg, by(treat)
Perform Fisher's exact test of the equality of the medians of mpg between
the two groups defined by treat
. median mpg, by(treat) exact
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Setup
. webuse medianxmpl
Perform Pearson chi-squared test of the equality of the medians of age
between the two groups defined by gender
. median age, by(gender)
Same as above command
. median age, by(gender) medianties(below)
Same as above command, but for observations with values of age equal to
the median, put them in the group above the median
. median age, by(gender) medianties(above)
Same as above command, but drop observations with values of age equal to
the median
. median age, by(gender) medianties(drop)
Same as above command, but for observations with values of age equal to
the median, divide them equally between the two groups
. median age, by(gender) medianties(split)
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Saved results
ranksum saves the following in r():
Scalars
r(N_1) sample size n_1
r(N_2) sample size n_2
r(z) z statistic
r(Var_a) adjusted variance
r(group1) value of variable for first group
r(sum_obs) actual sum of ranks for first group
r(sum_exp) expected sum of ranks for first group
median saves the following in r():
Scalars
r(N) sample size
r(chi2) Pearson's chi-squared
r(p) significance of Pearson's chi-squared
r(p_exact) Fisher's exact p
r(groups) number of groups compared
r(chi2_cc) continuity-corrected Pearson's chi-squared
r(p_cc) continuity-corrected significance
r(p1_exact) one-sided Fisher's exact p
References
Mann, H. B., and D. R. Whitney. 1947. On a test whether one of two random
variables is stochastically larger than the other. Annals of
Mathematical Statistics 18: 50-60.
Wilcoxon, F. 1945. Individual comparisons by ranking methods. Biometrics
1: 80-83.
Also see
Manual: [R] ranksum
Help: [R] signrank, [R] ttest
