# ANCOVAplot: One-way ANCOVA Judgement and Plot In PhDMeiwp/basicANCOVA: Basic One-Way ANCOVA Judgement and Plot

## Description

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.

## Usage

 ```1 2 3 4``` ```ANCOVAplot(x, y, groups, data, col = 1:length(levels(factor(groups))), pch = 1:length(levels(factor(groups))), lty = 1:length(levels(factor(groups))), Fig.slope = 1, xlab = NULL, ylab = NULL, legendPos = "topleft", ...) ```

## Arguments

 `x, y, groups` For covariate 'x', dependent 'y' and factor 'groups'. `data` The dataset contains three columns (x,y,groups) data. See an example via data("isotope",package = "basicANCOVA"). `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'. Whereas 'Fig.slope = 0', draw graph and output result of 'linear regression line' for each group. `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 `plot`,such as main, sub, xlab, ylab.

Weiping Mei

## References

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/ ).

`trendline`, `ancovaplot`
 ``` 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) ```