View source: R/anova_related.R

Many ANCOVAs | R Documentation |

Many ANCOVAs.

ancovas(y, ina, x, logged = FALSE)

`y` |
A matrix with the data, where the rows denote the observations and the columns are the variables. |

`ina` |
A numerical vector with 1s, 2s, 3s and so one indicating the two groups. Be careful, the function is desinged to accept numbers greater than zero. |

`x` |
A numerical vector whose length is equal to the number of rows of y. This is the covariate. |

`logged` |
Should the p-values be returned (FALSE) or their logarithm (TRUE)? |

Many Analysis of covariance tests are performed. No interaction between the factor and the covariate is tested. Only the main effects. The design need not be balanced. The values of ina need not have the same frequency. The sums of squares have been adjusted to accept balanced and unbalanced designs.

A matrix with the test statistic and the p-value for the factor variable and the covariate.

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr> and Manos Papadakis <papadakm95@gmail.com>.

D.C. Montgomery (2001). Design and analysis of experiments (5th Edition). New York: John Wiley \& Sons

```
ftests, ttests, anovas
```

## 100 variables, hence 100 F-tests will be performed y <- matrix( rnorm(90 * 100), ncol = 100 ) ina <- rbinom(90, 2, 0.5) + 1 x <- rnorm(90) system.time( a <- ancovas(y, ina, x) ) ## Not run: m1 <- lm(y[, 15] ~ factor(ina) + x) m2 <- lm(y[, 15] ~ x + factor(ina)) res<-anova(m1) res<-anova(m2) y <- NULL a[15, ] ## the same with the m2 model, but not the m1 ## End(Not run)

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