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:
2-way cross-tabulation tables
Various statistics that describe relationships between columns in the cross-tabulation
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
N-way cross-tabulation tables
N 2-way cross-tabulation tables
Statistics across and within strata
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 Example 3-36.
For details about the function arguments, invoke help(ore.freq)
.
Example 3-36 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 invokes 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 Example 3-36
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 1