The primary objective of a clinical trial is to determine whether a new treatment is effective in treating a specific condition.

Analysis of Variance (ANOVA) is a statistical method used to compare the means of two or more groups. It is commonly used in clinical trials to compare the outcomes of different treatments.

A meta-analysis is a statistical method used to combine the results of multiple studies to provide a more precise estimate of the effect of a treatment or intervention.

The incidence rate of a disease is the number of new cases of the disease that occur in a population over a specific time period.

A Kaplan-Meier curve is a graphical representation of the probability of survival over time. It is used in survival analysis to estimate the probability of survival for a specific population.

Logistic regression is a statistical method used to model the relationship between a binary outcome (e.g., presence or absence of a disease) and a set of independent variables (e.g., risk factors).

A receiver operating characteristic (ROC) curve is a graphical representation of the sensitivity and specificity of a diagnostic test at different cut-off values.

The Pearson correlation coefficient is a statistical measure of the linear relationship between two continuous variables.

A clinical decision rule is a set of criteria that clinicians use to make decisions about patient care. These rules are based on statistical evidence and are designed to improve the quality of care.

Kaplan-Meier curve, Cox proportional hazards model, and Log-rank test are all statistical methods used to analyze survival data in medical research.

A power analysis is a statistical method used to determine the sample size needed to achieve a desired level of statistical power in a clinical trial.

Logistic regression is a statistical method used to analyze the data from a case-control study in epidemiology. It is used to estimate the relationship between a disease and a set of risk factors.

A sensitivity analysis is a statistical method used to assess the robustness of the results of a statistical analysis. It is used to determine how sensitive the results are to changes in the assumptions or methods used in the analysis.

Cox proportional hazards model, Kaplan-Meier curve, and Log-rank test are all statistical methods used to analyze the data from a cohort study in epidemiology.

A meta-regression is a statistical method used to identify the factors that affect the results of a meta-analysis. It is used to determine how the results of a meta-analysis vary depending on the characteristics of the studies included in the analysis.