checkAvSd | R Documentation |

`checkAvSd`

compares if/how neighbour groups separate/overlap via the 'engineering approach' (+/- 2 standard-deviations is similar to a=0.05 `t.test`

).
This approach may be used as less elegant alternative to (multi-group) logistic regression.
The function uses 'daAv' as matrix of means (rows are tested for up/down character/progression) which get compared with boundaries taken from daSd (for Sd values of each mean in 'daAv').

```
checkAvSd(
daAv,
daSd,
nByGr = NULL,
multSd = 2,
codeConst = "const",
extSearch = FALSE,
outAsLogical = TRUE,
silent = FALSE,
callFrom = NULL
)
```

`daAv` |
matrix or data.frame |

`daSd` |
matrix or data.frame |

`nByGr` |
optinal specifying number of Elements per group, allows rather using SEM (adopt to variable n of different groups) |

`multSd` |
(numeric) the factor specifyin how many sd values should be used as margin |

`codeConst` |
(character) which term/word to use when specifying 'constant' |

`extSearch` |
(logical) if TRUE, extend search to one group further (will call result 'nearUp' or 'nearDw') |

`outAsLogical` |
to switch between 2col-output (separate col for 'up' and 'down') or simple categorical vector ('const','okDw','okUp') |

`silent` |
(logical) suppress messages |

`callFrom` |
(character) allow easier tracking of message(s) produced |

vector describing character as 'const' or 'okUp','okDw' (or if extSearch=TRUE 'nearUp','nearDw')

`rowGrpMeans`

```
mat1 <- matrix(rep(11:24,3)[1:40],byrow=TRUE,ncol=8)
checkGrpOrderSEM(mat1,grp=gl(3,3)[-1])
checkAvSd(rowGrpMeans(mat1,gl(3,3)[-1]),rowGrpSds(mat1,gl(3,3)[-1]) )
# consider variable n :
checkAvSd(rowGrpMeans(mat1,gl(3,3)[-1]),rowGrpSds(mat1,gl(3,3)[-1]),nByGr=c(2,3,3))
```

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