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diff --git a/tests/testthat/test_logistic.R b/tests/testthat/test_logistic.R
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+# Copyright (C) 2019 Johannes Ranke
+# Contact: jranke@uni-bremen.de
+
+# This file is part of the R package mkin
+
+# mkin is free software: you can redistribute it and/or modify it under the
+# terms of the GNU General Public License as published by the Free Software
+# Foundation, either version 3 of the License, or (at your option) any later
+# version.
+
+# This program is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+# FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more
+# details.
+
+# You should have received a copy of the GNU General Public License along with
+# this program. If not, see <http://www.gnu.org/licenses/>
+
+context("Fitting the logistic model")
+
+logistic <- mkinmod(parent = mkinsub("logistic"))
+
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+parms_logistic <- c(kmax = 0.08, k0 = 0.0001, r = 0.2)
+parms_logistic_optim <- c(parent_0 = 100, parms_logistic)
+d_logistic <- mkinpredict(logistic,
+  parms_logistic, c(parent = 100),
+  sampling_times)
+d_2_1 <- add_err(d_logistic,
+  sdfunc = function(x) sigma_twocomp(x, 0.5, 0.07),
+  n = 1, reps = 2, digits = 5, LOD = 0.1, seed = 123456)
+
+test_that("The logistic model fit is reproducible", {
+  m <- mkinfit("logistic", d_2_1[[1]], quiet = TRUE)
+  dtx <- endpoints(m)$distimes["parent", ]
+  expect_equivalent(dtx, c(36.86533, 62.41511), tolerance = 0.00001)
+})
+
+test_that("The logistic fit can be done via differential equation", {
+  # This is slow as we did not implement conversion to C
+  # because it is unlikely we will use the logistic model with metabolites
+  skip("Skip slow fit of logistic model using deSolve without compilation")
+  m_2 <- mkinfit("logistic", d_2_1[[1]], solution_type = "deSolve", 
+                 quiet = TRUE)
+  dtx_2 <- endpoints(m_2)$distimes["parent", ]
+  expect_equivalent(dtx_2, c(36.86533, 62.41511), tolerance = 0.00001)
+})