What statistical method can be used to compare the same group measured twice?

The T-test is the appropriate statistical method for comparing the same group measured twice, commonly referred to as a paired sample T-test or dependent T-test. This method is specifically designed to analyze the means of two related groups to determine if there is a statistically significant difference between them.

In the context of assessing pre-and post-intervention data or measurements taken at two different time points for the same subjects, the T-test takes into account the paired nature of the data. It evaluates whether the average difference between the paired observations is significantly different from zero.

This test is suitable for normally distributed data and requires the observations from both measurements to be continuous and paired, making it ideal for longitudinal studies or repeated measures on the same participants. By focusing on the same group across two time points, the T-test effectively controls for individual differences, allowing for a clearer understanding of the impact of the intervention or change being measured.

Using other methods, such as ANOVA, would be inappropriate in this scenario because ANOVA is typically used for comparing means across three or more groups. In contrast, chi-square tests focus on categorical data and assess associations rather than means, while regression analysis examines relationships between variables rather than directly comparing means of repeated measures. Thus, the T-test is