Viral load measures are often subjected to some upper and lower detection limits depending on the quantification assays; hence, the responses are either left or right censored and maybe mismeasured or missing at times of interest. Consecutive CD4 cell counts on the same subject may also be correlated. To address these incomplete data (censored or missing) problems as well as correlation, statistical models such as the mixed-effects model can take these into account. The main purpose of this study was to determine factors that influence viral load and CD4 cell counts in ART patients using the mixed-effects model. The random slope mixed-effects model results indicated that viral load had a significant association with follow-up time, adherence, weight, age, clinical stage, and adherence at different follow-up time points. More specifically, as the value of follow-up time, weight, and adherence at different follow-up time points increases, the mean viral load decreases significantly. As the value of age and clinical stage increases, the mean viral load also tends to increase significantly.