# Alternative Link Functions

Let’s take a look at the alternative link functions.

## We'll cover the following

## Logistic functions

In some cases, including this one, more than one link function can be used with a given distribution in a GLM. In the case of the binomial GLM, two common alternatives to the logistic function are the wonderfully abbreviated `cloglog`

**complementary log-log** **function** and the `probit`

function. We can create alternative versions of model `1`

by swapping the logistic link for the probit as follows:

```
m1_probit <- glm(cbind(killed, alive) ~ Dose, data = beetle,
binomial(link = "probit"))
```

As well as for the complementary log-log:

```
m1_cloglog <- glm(cbind(killed, alive) ~ Dose, data = beetle,
binomial(link = "cloglog"))
```

There are various ways in which we could compare these models, but we can take the opportunity to revisit the use of information criteria. In our example we’re using the `AIC`

. The sample size is 471, or the number of beetles tested.

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