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In any research study, statistical procedures are used to establish the effects of treatments on a study and to determine if the outcome was as a result of the treatments given and not due to chance. In the study of the antiretroviral pill to determine if Truvada: a combination of two antiretroviral agents, lowers the risk of infection by HIV, the study was carried among the gay men who are believed to be among the high risk groups. A comparative study was carried in which the group was divided into two categories and given different treatments. One group was put on a placebo while the other group was put on the actual drug. This enabled the establishment of the effect of the drug to determine if there was any difference between those who took the drug and those who did not take the drug.
To determine the effect of the drug, the total number of those who were infected after taking the drug was compared with the total number of those who were infected among the group which was put on a placebo. The percentage of risk reduction after using the drug was calculated from the difference between the total number of those infected after taking the drug and those who were infected after taking the placebo. Randomization was done in assigning the study subjects in five countries in order to minimize bias in the sample and enhance the significance of the study. Case follow ups was also done on those involved in the study to establish if there was compliance in taking the drugs as well as monitoring the side effects of the drug.
Based on the study findings, it was concluded that the total chance of risk reduction for infection with HIV among gay men who took Truvada was 44%. The study also established that the risk of infection also depends on the drug's compliance rate with those who are compliant registering a 90% less risk of infection. From this study, it was also established that the drug's compliance rate among the subjects was very poor among those who were given the drug with only 3 out of 34 found to have taken the drug. These findings suggest that the results were not appropriate as there was a very low compliance rate which makes it hard to determine whether the results obtained for those who took the drug were purely as a result of the drug or due to chance. Due to the failure to control the study in a manner that minimizes the limitations like poor compliance and dishonest as well as failure to repeat the treatments on the same subjects or a different sample, the findings of the study are not statistically significant at the statistically acceptable confidence levels.
Using the findings of the study to determine the statistical significance, if a contingency table is derived from the values observed after taking the drug and placebo as well as the values expected, and working the total values of both, the Chi- square value can be calculated from the results. After working out, the calculated Chi- square was found to be 10.24. Using the statistical Chi-square tables to tabulate the results at one degree of freedom as obtained from the contingency table at a confidence level of 0.05, the statistically significant level should be below 3.84; hence the calculated Chi-square is greater than the tabulated Chi-square. Assuming the null hypothesis was that the drug lowers the risk of HIV infection, this leads to a rejection of the null hypothesis hence the study has a low significant level.
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