Sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials, especially trails with possible high placebo effect. SPCD is conducted with two periods and subjects are randomized into three groups: 1) placebo in both periods, 2) placebo in the first period and active therapy in the second period, and 3) active therapy in both periods. Each period is analyzed separately then the data are pooled to yield a single p-value. We consider SPCD with binary outcomes and with time to event outcomes, where response is defined as a favorable event prior to the end of follow-up for a given period of SPCD. We show that for these cases, the usual test statistics from period 1 and 2 are asymptotically normal and uncorrelated under the null hypothesis, leading to a straightforward combined testing procedure. In addition, we show that the estimators of the treatment effects from the two periods are asymptotically normal and uncorrelated under the null and alternative hypotheses, yielding confidence interval procedures with correct coverage. Simulations and real data analysis demonstrate the utility of the binary and time to event SPCD.