Test for Equivalence of two time series

1. What is a 2 sample equivalence test?
2. How do you compare two time series data?
3. What statistical test is used for time series data?
4. How do you assess equivalence?

What is a 2 sample equivalence test?

The objective of a two-sample equivalence test is to determine whether the means of two populations are equivalent based on two independent samples from these populations; here “equivalent” means that the two means differ by a small pre-defined amount.

How do you compare two time series data?

ISSUE: How to compare two time series? VALUE COMPARISON: The values or observed values of the two series may be compared. Two cases may arise: (i) equal length of data, and (ii) unequal length of data. The degree of difference is the number of pair less 1, i.e. df = n - 1.

What statistical test is used for time series data?

Durbin-Watson test for autocorrelation

The Durbin-Watson (DW) test is commonly used for detecting lag-1 autocorrelation in time series.

How do you assess equivalence?

A very simple equivalence testing approach is the “two one-sided tests” (TOST) procedure (Schuirmann, 1987). In the TOST procedure, an upper (Δ_U) and lower (−Δ_L) equivalence bound is specified based on the smallest effect size of interest (SESOI; e.g., a positive or negative difference of d = . 3).