I have a simple two-factor measurement error model. There is a constraint on the variance of one of the latent factors that it be positive. It easily finds a solution using mxTryHard but the variance estimate is always negative. What is the point of using a constraint if it is not honored? The negative estimate then causes problems when I try to bootstrap confidence intervals. It complains about quantile missing values and NaNs and won't produce a result unless I remove the variance from the confidence interval list.
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