Log-Linear Model on Categorical Data of HIV Cases
Abstract
Categorical data is widely used in social, health, educational and psychological research. A contingency table is a form of presenting this data. One of them is about cases of being infected with the HIV virus. The log-linear model is an alternative for analyzing categorical data. In this study, HIV cases will be analyzed using a log-linear model grouped by gender, age and province. Apart from that, several log-linear models will be formed and the best model will be selected based on the likelihood ratio (G^2) statistical test. According to the results of the analysis and consideration of model complexity, (JK*P, JK*U, P*U) is the best model and fits the data because the p-value = 0.517 is greater than the real level α = 0.05. This means that the interaction between gender, age and province is significant. Studies and explanations about the HIV virus show that individuals between the ages of 25-49 years are more at risk of being infected with the virus. Examined by gender group, women were most infected with the virus, namely 513 people. Apart from that, West Papua is the province with the highest number of HIV infections compared to Maluku and North Maluku
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