Equivalence test formulation of one sample z-test
For a population mean, $$\theta$$ estimated by a sample mean:
H0: $$\theta \leq $$-d or $$\theta \geq$$ d and HA : -d $$ \leq \theta \leq$$ d
If ind equals 1 then we reject nonequivalence so -d $$\leq$$ $$\theta$$ $$\leq$$ d otherwise we accept the null hypothesis of equivalence for the given type II error, beta.
[TYPE INTO R THE DESIRED INPUTS D, N, MEAN AND BETA USING VALUES IN FORM BELOW].
beta <- 0.05 d <- 0.2 n <- 10 mean <- 0
[THEN COPY AND PASTE THE BELOW INTO R]
cv <- sqrt(qchisq(p=beta, df=1, ncp=n*d^2)) cv2 <- sqrt(n)*cv ind <- 0 if (mean < cv2) ind = 1 print(ind)