tests/testthat/test-fit_ezddm.R

context("test-fit_ezddm")

# test_that("fit_ezddm works as intended", {
#   library(rtdists)
#   data1 <- rdiffusion(n = 100, a = runif(1, 2, 4), v = runif(1, -3, 3), t0 = runif(1, 0.3, 0.5), z = 0.5 * 2) # simulate data
#   data2 <- rdiffusion(n = 100, a = runif(1, 2, 4), v = runif(1, -3, 3), t0 = runif(1, 0.3, 0.5), z = 0.5 * 2) # simulate data
#   dataAll <- rbind(data1, data2) # join data
#
#   dataAll$response_char <- dataAll$response
#   dataAll$response <- ifelse(dataAll$response == "upper", 1, 0) # convert responses to 1 and 0
#   dataAll$subject <- rep(c(1, 2), each = 100) # assign subject id
#
#   dataAll$cond1 <- base::sample(c("a", "b"), 200, replace = TRUE) # randomly assign conditions a/b
#   dataAll$cond2 <- base::sample(c("y", "z"), 200, replace = TRUE) # randomly assign conditions y/z
#
#   # fit model to just entire data set (assumes all data came from 1 subject)
#   # a <- fit_ezddm(data = dataAll, rts = "rt", responses = "response")
#   # expect_equal(a[, .N], 1)
#   # fit model to just entire data set (assumes all data came from 1 subject)
#   # b <- fit_ezddm(data = dataAll, rts = "rt", responses = "response", id = "subject")
#   # expect_equal(b[, .N], 2)
#   # fit model to each subject by cond1
#   # c <- fit_ezddm(data = dataAll, rts = "rt", responses = "response", id = "subject", group = "cond1")
#   # expect_equal(c[, .N], 4)
#   # fit model to each subject by cond1,cond2
#   # d <- fit_ezddm(data = dataAll, rts = "rt", responses = "response", id = "subject", group = c("cond1", "cond2"))
#   # expect_equal(d[, .N], 8)
#
#   dataAll$rt <- dataAll$rt * runif(nrow(dataAll), 100, 2000)
#   expect_error(fit_ezddm(data = dataAll, rts = "rt", responses = "response"))
#
# })
hauselin/hausekeep documentation built on Feb. 3, 2023, 3:09 p.m.