5.2.5 Analyze the Frequency of Cross-Tabulations
The ore.freq function analyses the output of the ore.crosstab function and automatically determines the techniques that are relevant to an ore.crosstab result.
The techniques depend on the kind of cross-tabulation tables, which are the following:
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2-way cross-tabulation tables
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Various statistics that describe relationships between columns in the cross-tabulation
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Chi-square tests, Cochran-Mantel-Haenzsel statistics, measures of association, strength of association, risk differences, odds ratio and relative risk for 2x2 tables, tests for trend
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N-way cross-tabulation tables
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N 2-way cross-tabulation tables
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Statistics across and within strata
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The ore.freq function uses Oracle Database SQL functions when available.
The ore.freq function returns an ore.frame in all cases.
Before you use ore.freq, you must calculate crosstabs, as shown in the following example.
For details about the function arguments, call help(ore.freq).
Example 5-41 Using the ore.freq Function
This example pushes the iris data set to the database and gets the ore.frame object iris_of. The example gets a crosstab and calls the ore.freq function on it.
IRIS <- ore.push(iris) ct <- ore.crosstab(Species ~ Petal.Length + Sepal.Length, data = IRIS) ore.freq(ct)
Listing for This Example
R> IRIS <- ore.push(iris)
R> ct <- ore.crosstab(Species ~ Petal.Length + Sepal.Length, data = IRIS)
R> ore.freq(ct)
$`Species~Petal.Length`
METHOD FREQ DF PVALUE DESCR GROUP
1 PCHISQ 181.4667 84 3.921603e-09 Pearson Chi-Square 1
$`Species~Sepal.Length`
METHOD FREQ DF PVALUE DESCR GROUP
1 PCHISQ 102.6 68 0.004270601 Pearson Chi-Square 1Parent topic: Explore Data