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Central Statistical Monitoring (CSM) is gaining widespread recognition for its contribution to improving data integrity and regulatory compliance in clinical trials. While the existing literature offers numerous approaches based on fundamental statistical techniques, many of these methods exhibit notable limitations and shortcomings.

Confidence intervals (CI) are part of inferential statistics that help in making inference about a population from a sample. Based on the confidence level, a true population mean is likely covered by a range of values called confidence interval.

Assume you have a data frame (df) for patients taking a specific drug. The data consists of a factor variable (Drug) and a numeric variable (N_patients). Drugs N_patients Drug 1 50 Drug 2 40 Drug 3 23 Drug 4 92 Drug 5 70 Later on you filter the data frame for specific levels in the factor variable and saved it in a new data frame called df1.

The data pertaining to cases, deaths and recoveries is pooled from Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE). Vaccination data is pooled from Our world in data.

It took Scientists ~ 10 months to come up with the vaccine against Covid-19. Now its up to governments and people’s awareness to help eradicate the virus. For this reason this shinyapp helps monitor the vaccination status of the countries that have initiated vaccinations.