Constructs a repeated measures ANOVA model.

1 |

`DV` |
either a |

.

`family` |
a |

`between` |
(optional) either a |

`within` |
either a |

`N` |
a vector with the number of observations in each cell of the design. |

`mu` |
a matrix with the means in each cell of the design. |

`bsigma` |
a vector with the standard deviations in each cell of the between design. |

`wsigma` |
a vector with the standard deviations in each cell of the within design. |

`nu` |
a vector with the standard deviations in each cell of the within design. |

`tau` |
a vector with the standard deviations in each cell of the within design. |

`id.name` |
a string with the name of the variable used to differentiate subjects. |

`display.direction` |
a string indicating whether the data will be in long or wide format (internally, the model always uses a long format.) |

The rmANOVA function constructs a repeated measures ANOVA model.

An object of class `rmANOVA`

(directly extending the SimDatModel class).

Maarten Speekenbrink

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
# a 2*2*2*2 factorial ANOVA with repeated measures on the last two factors
mod <- rmANOVA(between=data.frame(A=factor(c(1,1,2,2),labels=c("A1","A2")),B=factor(c(1,2,1,2),labels=c("B1","B2"))),within=data.frame(V=factor(c(1,1,2,2),labels=c("V1","V2")),W=factor(c(1,2,1,2),labels=c("W1","W2"))),N=rep(10,4),mu=cbind(c(0,1,2,3),c(1,2,3,4),c(3,4,5,6),c(6,7,8,9)),bsigma=c(1,1,1,1),wsigma=c(1,1,1,1),nu=NULL,tau=NULL,DV=list(name="Y",min=-Inf,max=Inf,digits=8),family=NO(),id.name="ID",display.direction=c("wide","long"))
mod <- simulate(mod)
# a completely within ANOVA
mod <- rmANOVA(within=data.frame(V=factor(c(1,1,2,2),labels=c("V1","V2")),W=factor(c(1,2,1,2),labels=c("W1","W2"))),N=rep(1000,1),mu=matrix(c(0,1,2,3),nrow=1),bsigma=c(100),wsigma=c(1,1,1,1),nu=NULL,tau=NULL,DV=list(name="Y",min=-Inf,max=Inf,digits=8),family=NO(),id.name="ID",display.direction=c("wide","long"))
mod <- simulate(mod)
# create two factors and put them into a variablelist
f1 <- NominalVariable(factor(c(1,1,2,2),labels=c("A1","A2")),name="A")
f2 <- NominalVariable(factor(c(1,2,2,3),labels=c("B1","B2","B3")),name="B")
bdesign <- VariableList(list(f1,f2))
# create two factors and put them into a variablelist
f1 <- NominalVariable(factor(c(1,1,2,2),labels=c("W1","W2")),name="W")
f2 <- NominalVariable(factor(c(1,2,1,2),labels=c("V1","V2")),name="V")
wdesign <- VariableList(list(f1,f2))
# and a random interval variable
d <- RandomIntervalVariable(numeric(1),name="Y",min=-10,max=Inf,digits=2)
# means
mu <- cbind(c(10,15,15,20),c(20,25,25,30),c(10,15,15,20),c(30,25,20,25))
mod2 <- rmANOVA(DV=d,family=NOF(),between=bdesign,within=wdesign,N=rep(15,4),mu=mu,bsigma=c(2,3,4,5),wsigma=c(1,2,3,4),nu=c(1,1,1,1))
mod2 <- simulate(mod2)
``` |

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