INSIDA survey: basic description of variables used in the final model.

<p>INSIDA survey: basic description of variables used in the final model.</p

Comparison of marginal model, and full-shared, partial-shared and partial-equal random effects models, all without or with common intercept and common slope for HIV prevalence and wealth index for the models for <i>π</i>_<i>F</i> and <i>π</i>_<i>M</i>.

<p>The column ‘-2ll’ shows the values of -2×log-likelihood; the column ‘#Par’ shows the number of parameters and the columns ‘Rank’ refers to the ranking of the models according to the AIC and BIC criterion.</p

Parameters estimates and standard error estimates for the CE-PE model.

<p>Parameters estimates and standard error estimates for the CE-PE model.</p

Joint models for mixed categorical outcomes: a study of HIV risk perception and disease status in Mozambique

<p>Two types of bivariate models for categorical response variables are introduced to deal with special categories such as ‘unsure’ or ‘unknown’ in combination with other ordinal categories, while taking additional hierarchical data structures into account. The latter is achieved by the use of different covariance structures for a trivariate random effect. The models are applied to data from the INSIDA survey, where interest goes to the effect of covariates on the association between HIV risk perception (quadrinomial with an ‘unknown risk’ category) and HIV infection status (binary). The final model combines continuation-ratio with cumulative link logits for the risk perception, together with partly correlated and partly shared trivariate random effects for the household level. The results indicate that only age has a significant effect on the association between HIV risk perception and infection status. The proposed models may be useful in various fields of application such as social and biomedical sciences, epidemiology and public health.</p

Joint models for mixed categorical outcomes: a study of HIV risk perception and disease status in Mozambique

<p>Two types of bivariate models for categorical response variables are introduced to deal with special categories such as ‘unsure’ or ‘unknown’ in combination with other ordinal categories, while taking additional hierarchical data structures into account. The latter is achieved by the use of different covariance structures for a trivariate random effect. The models are applied to data from the INSIDA survey, where interest goes to the effect of covariates on the association between HIV risk perception (quadrinomial with an ‘unknown risk’ category) and HIV infection status (binary). The final model combines continuation-ratio with cumulative link logits for the risk perception, together with partly correlated and partly shared trivariate random effects for the household level. The results indicate that only age has a significant effect on the association between HIV risk perception and infection status. The proposed models may be useful in various fields of application such as social and biomedical sciences, epidemiology and public health.</p

Comparison of hematology reference ranges derived from young adults in Maputo, Mozambique with those from other countries.

b<p>values corresponding to individuals aged 13–34 years.</p><p>NA – Not available.</p

Hematology reference ranges (median and 2.5^th- 97.5^thpercentiles) derived from young adults in Maputo, Mozambique.

<p>p-values indicate comparisons between males and females</p

Prevalence of the Major Diagnostic Errors by Pathology at Autopsy

<p>Prevalence of the Major Diagnostic Errors by Pathology at Autopsy</p

Comparison of chemistry reference ranges derived from young adults in Maputo, Mozambique compared with those from western Kenya and the United States of America.

<p>NA – Not available.</p

Lymphocyte reference ranges from youth in Maputo, Mozambique compared with sources from Africa and the United States of America.

a<p>Reference ranges provided by Becton-Dickinson with the MultiTEST IMK Kit Reagent package.</p><p>NA – Not available.</p