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multivar
output
Run multivar
by typing:
multivar polyem_90_par |
The output from multivar
is straightforward. Toward the end,
there are the parameter estimates and the log-likelihood from the last
iteration of the EM algorithm. If you chose to fit a null (purely
environmental) model, the parameter estimates and log-likelihood are
also given. A likelihood ratio test can be used. A conservative test is
provided by comparing the test statistic to a chi-squared distribution, with
the degrees of freedom being the difference in the numbers of estimated
parameters between these two models.
iteration #201: additive variance estimates (traits 1, 2) 0.816 0.037 covariances 0.138 residual variance estimates (traits 1, 2) 0.223 0.610 covariances -0.239 trait 1 overall mean -0.063 trait 2 overall mean 1.780 fixed effect 1 -0.717 0.546 fixed effect 2 -1.008 -0.552 1.167 current log-likelihood = -183.098 estimates of environmental model residual variance estimates (traits 1, 2) 1.136 0.642 covariances -0.102 trait 1 overall mean 0.062 trait 2 overall mean 1.801 fixed effect 1 -0.773 0.589 fixed effect 2 -1.010 -0.553 1.170 environmental model log-likelihood = -197.799 |