NOEC | R Documentation |

calculating the NOEC and LOEC using Dunnett's test

NOEC(x, rspn, blankC = FALSE, sigLev = 0.05, alternertive = 'B', sav = FALSE)

`x` |
a numeric vector of experimental concentrations |

`rspn` |
a numeric matrix of experimental responses with at least three replicates. |

`blankC` |
TRUE if rspn contains responses of blank control. The default is FALSE. |

`sigLev` |
the significance level for Dunnett's test. The default is 0.05. |

`alternertive` |
the alternative hypothesis: "U"=upper one-sided test; "B"=two-sided test(default). |

`sav` |
TRUE: save output to a default file; FALSE: output will not be saved; a custom file directory: save output to the custom file directory. |

Dunnett's test (Dunnett, 1964) is performed to compare the treatment groups with the
blank controls. The critical constants (store in DTcv) were calculated using step-down
Dunnett test procedure. Three significance level (0.01, 0.05, and 0.1) are supported.
## Q: One dataset has four blank controls (C1, C2, C3, C4) and one treatment has three
replicates (T1, T2, T3),
## another treatment has five replicates (R1, R2, R3, R4, R5), how to arrange the
response matrix (rspn)?
## A: Label the missing values as NA, the response matrix (rspn) can be arranged as follows:

C1 C2 C3 C4 NA

T1 T2 T3 NA NA

R1 R2 R3 R4 R5

The adjustation of critical value for the unequal variances or unequal number of control and replicates is skipped in this program.

`mat ` |
information on Dunnett's test.DT: Dunnett's test values; DTcv: critical values for Dunnett's test at the significance level of sigLev. |

`noec ` |
non-observed effect concentration (NOEC). |

`loec ` |
least-observed effect concentration (LOEC). |

`sigLev ` |
the significance level used in the Dunnett's test. |

`DF ` |
the number of treatments and degree of fredom. |

`sav` |
TRUE: save output to a default file; FALSE: output will not be saved; a custom file directory: save output to the custom file directory. |

x a vector of concentrations or levels in an ascending order. response matrix with at least 3 replicates. if the response matrix (rspn) contains blank controls (blankC = TRUE), the blank controls should be allocated in the first tow of rspn matrix. missing values should be labled as NA.

Dunnett, C.W., 1964. New tables for multiple comparisons with a control. Biometrics 30, 482-491.

## example 1 # calcualte the NOEC and LOEC of heavy metal Ni(2+) on the MCF-7 cells at the default significance # level of 0.05 x <- cytotox$Ni$x rspn <- cytotox$Ni$y NOEC(x, rspn) ## example 2 # calcualte the NOEC and LOEC of Neomycin sulfate on the phtotobacteria at the significance # level of 0.01 x <- antibiotox$NEO$x rspn <- antibiotox$NEO$y NOEC(x, rspn, sigLev = 0.01)

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