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To confirm this relation, we next perform multivariate estimation of the relation between illiquidity and returns.
Thus our generalized linear model is an appropriate alternative for performing the multivariate estimation of the prevalence ratio.
Based on these reliabilities, effective own performances (EOP) were calculated and used as weighting factors for yield deviations in the multivariate estimation of breeding values for method YD.
Full multivariate estimation of all traits based on phenotypic data could represent the optimum methodology [ 5- 7], but in routine genetic evaluations substantial restrictions (e.g. computer power and computational considerations) make this approach infeasible.
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We anticipate that penalized maximum likelihood estimation will become part of our everyday toolkit, as truly multivariate estimation for quantitative genetic problems becomes routine.
Table 2 shows the results of an attempt to establish factors influencing condom use through multivariate estimation for the full sample and for males and females separately.
We only report those explanatory variables which were significant for each model in the table to simplify the presentation even though the multivariate estimation included all of the explanatory variables.
A variety of multivariate estimation methods are now available to the meta-analyst, so an assessment of the sensitivity of the model fit to the procedure used may easily be performed.
It should become part of our everyday toolkit for multivariate estimation in quantitative genetics.
Multivariate analyses and estimation of 95% CI were not conducted if the sample size of interest was less than 30, as the estimate is considered unreliable under NAMCS and NHAMCS analysis recommendations [17].
Cox proportional hazards modeling accounting for left truncation was used for univariate and multivariate analyses with estimation of HRs and 95%% CIs.
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