library(timeDate)
library(ggplot2)

pA <- 0.052
pB <- 0.055
nA <- 10000
nB <- 10000
alpha <- 0.05

set.seed(47849)
data <- data.frame(group = rep(c("A", "B"), c(nA, nB)),
                   timestamp = sample(seq(as.timeDate('2016-06-02'),
                                          as.timeDate('2016-06-30'), by = 1), nA+nB),
                   clickedTrue = as.factor(c(rbinom(n = nA, size = 1, prob = pA),
                                             rbinom(n = nB, size = 1, prob = pB))))

#  сортировка по timestamp
data <- data[order(data$GMT.x..i..), ]
levels(data$clickedTrue) <- c("0", "1")

# считаем pval итеративно
pValues <- c()
index <- c()
presentData <- matrix()
for (i in 50:dim(data)[1]){
  presentData <- table(data$group[1:i], data$clickedTrue[1:i])
  if (all(rowSums(presentData) > 0)){
    pValues <- c(pValues, t.test(presentData)$p.value)
    index <- c(index, i)
  }
}
results <- data.frame(index = index,
                      pValue = pValues)

# рисуем
ggplot(results, aes(x = index, y = pValue)) +
  geom_line() +
  geom_hline(aes(yintercept = alpha)) +
  scale_y_continuous(name = "p-value", limits = c(0,1)) +
  scale_x_continuous(name = "наблюдения") +
  theme(text = element_text(size=20)) +
  theme_classic()