Modeling HIVAIDS Variables, A Case Of Contingency Analysis
Hypothesis testing may be performed on contingency tables in order to decide whether or not effects are present. Effects in a contingency table are defined as relationships or interactions between variables of interest. However, considering the number of adolescence patients diagnosed of HIV/AIDS within a short frame of time in BSH, Nsukka, the researcher was moved to carry out a study to actually confirm whether patients’ diagnosed of the aliment have any association based on their gender, years and age of diagnoses. The observation from the hypotheses carried out on this study using X2 statistic, was that none of the variables of interest considered were dependent of each other. Gender (X) and age (Y) of patients diagnosed of HIV/AIDS in the Bishop Shanahan Missionary Hospital, Nsukka (B.S.H) are independent of the years (Z) of affection. Also the conditional independence of the pair-wise variables of interest existed. Age (Y) is conditionally independent of both gender (X) of the affected patient and the year (Z) of the affection. Moreover, gender (X) is conditionally unrelated to both the year (Z) of affection and the age of the affected patients and lastly, year of affection has no conditional interaction with both the gender (X) and age (Y) of the affected patients.
Keywords: Modeling, Contingency, Independency, Chi-square, HIV/AIDS