Assessment of tuberculosis treatment accessibility for patients co-infected or not with the human immunodeficiency virus

This study aimed to evaluate accessibility to treatment for people with TB co-infected or not with HIV. This cross-sectional study addressed issues regarding accessibility to treatment in a city in the interior of Sao Paulo state, Brazil. The instrument Primary Care Assessment Tool was utilized with 95 people. To evaluate access to treatment, Student's t test was used. The mean scores of variables were analyzed separately and compared between two groups (people with TB co-infected with HIV and people with TB not co-infected with HIV). Mean scores showed that HIV co-infected people presented greater difficulties in gaining access than those not co-infected. Professionals visited co-infected people more often when compared to those not co-infected; the co-infected people almost never accessed treatment for their disease in the Health Unit nearest their home. There is, therefore, the need for greater integration and communication between the programs for treatment of Tuberculosis and STD/AIDS.

Assessment of variance components in nonlinear mixed-effects elliptical models

The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.