What are Common Inferential Statistical Methods Used?
Several inferential statistical methods are commonly used in the study of neonatal disorders, including:
Hypothesis Testing Hypothesis testing involves making an assumption about a population parameter and using sample data to test this assumption. For example, researchers may hypothesize that a new intervention reduces the incidence of neonatal sepsis. Using sample data, they can perform tests such as the t-test or chi-square test to determine if there is significant evidence to support this hypothesis.
Confidence Intervals Confidence intervals provide a range of values within which the true population parameter is likely to lie. For instance, a study might report that the prevalence of preterm birth in a sample is 10% with a 95% confidence interval of 8% to 12%. This means that researchers are 95% confident that the true prevalence in the population falls within this range.
Regression Analysis Regression analysis helps in understanding the relationship between dependent and independent variables. For example, logistic regression can be used to identify risk factors for neonatal mortality by examining variables such as birth weight, gestational age, and maternal health.
Survival Analysis Survival analysis is used to analyze time-to-event data, such as the time until a newborn develops a particular disorder or the time until recovery. This method is particularly useful for studying longitudinal studies in neonatology.
