Dear all,

I cannot find the R command to get the unconditional probability in a probit model.

Can anyone help, please?

Dear all,

I cannot find the R command to get the unconditional probability in a probit model.

Can anyone help, please?

Can you say more about what you mean by "unconditional probability"? You can get the predicted probabilites of the outcome for the data used to fit the model by running `predict(my_model, type="response")`

(where `my_model`

is the probit model object returned by the `glm`

function). You can get predicted probabilities for new data by providing a new data frame to `predict`

that has values of the independent variables at which you want predictions, for example, `predict(my_model, newdata=my_new_data, type="response")`

.

If you're interested in marginal effects, you could look at the `margins`

package, which has functions for extracting marginal effects from generalized linear models.

We can provide help specifically tailored to your problem if you can provide a data sample and the code you ran (see here for help on how to provide a reproducible example).

Many thanks! I am aware of the margins package.

I have a sample of target firms and non-targe firms. I want the unconditional probability for a firm being

targeted during my sample period.

I'm not understanding what you mean by "unconditional". The model will tell you the predicted probability of a firm being targeted, given (i.e., conditional on) specific values of the covariates in your model. The `predict`

function can give you these predicted probabilities. Is that what you're trying to determine?

Ok! I will have a look into the predict() function!

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