Description Usage Arguments Author(s) References See Also Examples

Judge whether the input data set met the key assumptions for underlie the use of one-way analysis of covariance (ANCOVA). The assumptions include (i) linearity of regression between the dependent variable 'y' and covariate 'x'; (ii) homogeneity of regression slopes among groups (Miller and Chapman, 2001). After judgement, then we continue ANCOVA analysis and plot.

1 2 3 4 |

`x, y, groups` |
For covariate 'x', dependent 'y' and factor 'groups'. |

`data` |
The dataset contains three columns (x,y,groups) data. |

`col, pch, lty` |
The color, pch and linetype for plot. |

`Fig.slope` |
If 'Fig.slope = 1', draw graph and output the result of 'ANCOVA with same slope'. |

`xlab, ylab` |
The labels of x-axis and y-axis. |

`legendPos` |
The position of legend, such as one of c("none","bottomright","bottom","bottomleft","left","topleft","top","topright","right","center"). |

`...` |
additional parameters to |

Weiping Mei

The judging criteria is mainly contributed by

Gregory A. Miller and Jean P. Chapman. (2001). Misunderstanding analysis of covariance. Journal of Abnormal Psychology, 110(1), 40-48. Doi 10.1037//0021-843x.110.1.40

The interpretations of output results are mainly contributed by

Salvatore S. Mangiafico. (2015). An R Companion for the Handbook of BiologicalStatistics, s, version 1.3.2. rcompanion.org/documents/RCompanionBioStatistics.pdf . (Web version: rcompanion.org/rcompanion/ ).

1 2 3 4 5 6 7 8 9 10 11 | ```
library(basicANCOVA)
data("isotope",package = "basicANCOVA")
# (same slope) output ANCOVA results and graphic
ANCOVAplot(x = isotope$d13C, y = isotope$d15N, groups = isotope$area,
data = isotope, Fig.slope = 1) # (same slope) output ANCOVA results and graphic
# Not run
ANCOVAplot(x = isotope$d13C, y = isotope$d15N, groups = isotope$area,
data = isotope, Fig.slope = 0) # (different slopes) output "linear regression" results of each group and graphic
# End (Not run)
``` |

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