Hi Huiying,

Question 1: MO wasn't really designed for binary variables with measurement error and so there isn't really a proper way to specify the prior mean/SD. If you have validation (gold-standard) data, you include both the validated and misclassified/mismeasured variable in the same amelia model and get imputations that way. Otherwise, you could try to force amelia to handle this situation by setting the prior mean to either 0 or 1 with some SD that reflects your uncertainty and then manually force the imputations to be either 0 or 1 after the imputations.

Question 2: moPrep is a convenience function that sets up the priors and overimp arguments in the right way. So you should get the same imputations either way (except for the randomness of the imputations themselves).

Cheers,

Matt

~~~~~~~~~~~

Matthew Blackwell

Assistant Professor of Government

Harvard University

url: http://www.mattblackwell.org

On Tue, May 31, 2016 at 5:21 AM, HuiYing Chua <hyc.tartoon@gmail.com> wrote:

Hi there,

I have basically 2 questions related to setting observation-level priors on nominal variables.

I am trying to do an overimputation on a dichotomous variable, say y1.

My 1st question:

I am aware that using the argument “priors” and “overimp”, I could specify observation-level priors by 4-column matrix (row, column, prior.mean, prior.sd) or 5-column matrix (row, column, lower confidence range, upper confidence range, confidence level). I am attempting the 4-column matrix but I am not sure how do I specify prior.mean and prior.sd when my prior is the dichotomous variable itself. I read somewhere prior.mean can be set to y1 itself? Is prior.sd similar to the proportion of variance attributable to measurement error? Would need advice on how do I specify prior.sd in this case.

My 2nd question:

I am also aware of generating prior using the command “moPrep” from the Amelia package. The argument “error.proportion” from “moPrep” command is rather easy to understand (proportion of variance attributable to measurement error). But what is the difference setting priors using “moPrep" and “priors”? Should the output be the same?

Please kindly advice. Many many thanks !

Huiying

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