*Bounty: 50*

I’m trying to run a multivariate multiple regression in R, i.e. including multiple predictors and multiple outcome variables in the same linear regression model. **Does anybody know how to pull out the coefficients and p-values for the relationship between each predictor and outcome pair in a multivariate multiple regression?** I cannot seem to work out how to do that (I’ve been trying!).

Let me explain with an example dataset, if it helps:

```
#Create example dataset
df <- data.frame(pid=factor(501), y1=numeric(501), y2=numeric(501),
y3=numeric(501), y4=numeric(501), x1=factor(501), x2=factor(501),
x3=factor(501), x4=numeric(501), x5=numeric(501))
df$pid <- seq(1,501, by=1)
df$y1 <- seq(1,101, by=0.2)
df$y2 <- seq(401,201, by=-0.4)
df$y3 <- sqrt(rnorm(501, 7, 0.5))^3
df$x1 <- c(rep(c("sad","happy"), each=250), "sad")
df$x2 <- c(rep(c("human","vehicle","animal"), each=167))
df$x3 <- c(rep(seq(1,10, by=0.1), each=5), seq(1,46, by=1))
df$x4 <- rnorm(501, 3, .24)
df$x5 <- sqrt(rnorm(501, 23, 3.5))
```

I then create the model using this:

```
#Specify the regression model
model <- lm(cbind(y1, y2, y3) ~ x1 + x2 + x3 + x4 + x5, data=df)
```

I can’t simply use `summary(lm)`

as doing so runs separate regressions without accounting for familywise error, nor does it account for the dependent variables possibly being correlated.

Reiterating my question. **Does anybody know how to pull output so I can work out the coefficient and p-values but doing so in the same model?** For example, I want to work out the coefficients and p-values of:

```
x1, x2, x3, x4 and x5 on y1
x1 and x2 on y2
x1, x2, x3, x4 and x5 on y3
... etc etc
```

I tried the `car`

package:

```
modelanova <- car::Anova(model)
summary(modelanova)
```

However, I couldn’t get it to break down to a particular outcome variable, it’d only produce coefficients overall (as if a composite outcome variable had been created)

Any ideas would be wonderful. I know I could run several univariate multiple regressions but I am particularly interested in running a single multivariate multiple regression.

Get this bounty!!!