Dear all, I need to obtain standard errors and MEMs (Marginal effects computed at the mean) after run the command in ordered logit model.
I have a ordered logit model with six categories for dependent variable.
I estimated the model using the command ologit. I need to obtain the Marginal effects computed at the mean of all variables as an approximation of average marginal effects and their standar errors. I Know I can used the command mchange but I don` t if I have to use "mchange" command or "mchange atmeans".
I don`t know what exaclty is the difference between using: "mchange, atmeans" or just "mchange" after run my model.
Moreover, my key question is to obtain standard errors for marginal effects. How can I get standard errors after run the command "mchange, atmeans"?
I only can I obtain standard errors if I run just mchange, stats(all) after my model, but not using mchange, atmeans. I need obtain the Marginal effects computed at the mean of all variables (MEMs) and their corresponding standar errors.
In the attachment you can see an example with my results.
Thank you very much
I have a ordered logit model with six categories for dependent variable.
I estimated the model using the command ologit. I need to obtain the Marginal effects computed at the mean of all variables as an approximation of average marginal effects and their standar errors. I Know I can used the command mchange but I don` t if I have to use "mchange" command or "mchange atmeans".
I don`t know what exaclty is the difference between using: "mchange, atmeans" or just "mchange" after run my model.
Moreover, my key question is to obtain standard errors for marginal effects. How can I get standard errors after run the command "mchange, atmeans"?
I only can I obtain standard errors if I run just mchange, stats(all) after my model, but not using mchange, atmeans. I need obtain the Marginal effects computed at the mean of all variables (MEMs) and their corresponding standar errors.
In the attachment you can see an example with my results.
Thank you very much
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