This function calculates the conditional probability of deviation of two centrality measures (or any two other continuous variables) from their corresponding means in opposite directions.

`cond.prob.analysis(data, nodes.colname, Desired.colname, Condition.colname)`

- data
A data frame containing the values of two continuous variables and the name of observations (nodes).

- nodes.colname
The character format (quoted) name of the column containing the name of observations (nodes).

- Desired.colname
The character format (quoted) name of the column containing the values of the desired variable.

- Condition.colname
The character format (quoted) name of the column containing the values of the condition variable.

A list of two objects including the conditional probability of deviation of two centrality measures (or any two other continuous variables) from their corresponding means in opposite directions based on both the entire network and the split-half random sample of network nodes.

Other centrality association assessment functions:
`double.cent.assess.noRegression()`

,
`double.cent.assess()`

```
MyData <- centrality.measures
My.conditional.prob <- cond.prob.analysis(data = MyData,
nodes.colname = rownames(MyData),
Desired.colname = "BC",
Condition.colname = "NC")
```