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| Simulating heteroscedasticity |
 
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I am trying to do a monte carlo simulation study of a regression model with heteroscedasticity, and cannot figure out how to simulate the heteroscedasticity. When I model heteroscedasticity in Mplus, I do so using the MODEL CONSTRAINT feature, which is unavailable in specifying the model population.
I know that I can use a mixture model to create heteroscedasticity, but would like to more precisely control how the residual variance changes. Is this possible in Mplus? |
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| See our new book described on our website. Heteroscedasticity scripts are shown for Chapter 1. |
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Thank you for your response, I now see that heteroscedasticity can be introduced using a random slopes model.
However, in these models, it seems that the heteroscedasticity is always symmetric (large residual variance at the extremes, low residual variance at the center). Is there a way to simulate a population for the model in ex1.15.inp in which the residual variance is a+bx? Thanks again for your help |
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| The random slopes approach doesn't necessarily have large variances at the extremes if one focuses on a certain range of x values relevant for the application. That's how it is applied in Chapter 1 where the variance is low for low x values and high for high x values. This approach provides an easy way to generate heteroscedastic data. I am not sure how data could be generated using the ex1.15 approach; seems like you would have to generate data for each of a set of distinct x values with different residual variance and then combine. |
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