conNEcT {ConNEcT} | R Documentation |

## Calculate the link strength between multiple behaviors and return them as a matrix (optionally discarting all non-significant links)

### Description

Calculate the link strength between multiple behaviors and return them as a matrix (optionally discarting all non-significant links)

### Usage

```
conNEcT(
data,
lag = 0,
conFun,
test = FALSE,
typeOfTest = "permut",
adCor = TRUE,
nBlox = 10,
nReps = 100,
signLev = 0.05
)
```

### Arguments

`data` |
Binary time-points-by-variable matrix |

`lag` |
Non-negative integer indicating how many time points the second variable is lagged (default 0) |

`conFun` |
Contingency measure function (calculating the contingency value between two binary vectors). Built in: funPropAgree, funClassJacc, funKappa, funCorrJacc, funOdds, funLogOdds, funPhiCC |

`test` |
Logic indicationg whether a significance test is executed (TRUE) or not (FALSE;default) |

`typeOfTest` |
String indicating whether a model-based ('model') or a permutation-based ('permut'; default) data generation approach is used. |

`adCor` |
Logic indicating the auto-dependence correction should be applied (TRUE; default) or not (FALSE) |

`nBlox` |
Number indicating the number of segments (default 10). Necessary for permutation-based test, accounting for auto-dependence (typeOfTest='permut'; adCor=TRUE) |

`nReps` |
Number of replicates/samples that is used to generate the test distribution |

`signLev` |
Significance level of the test (default 0.05) |

### Value

A conNEcT-object including

`allLinks`

Matrix of pairwise calculated contingency measures

`signLinks`

Matrix of pairwise calculated contingency measures containing only significant links
(others are set to 0)

`pValue`

P-values for the one-sided upper significance test

`para`

Parameter settings containing
`lag`

, `test`

,`typeOfTest`

,
`adCor`

, `nBlox`

, `nReps`

,
`funName`

, and `varNames`

`probs`

Table of relative frequency and auto-dependency

### Examples

```
netdata=cbind(rep(c(1,1,1,1,1,0,0,0,0,0),100),
rep(c(0,0,1,1,1,1,0,0,0,0),100))
conNEcT(netdata,lag=1,conFun=funKappa,test=TRUE,nBlox=5)
```

*ConNEcT*version 0.7.27 Index]