notebooks/case_studies/BEST.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bayesian Estimation Supersedes the T-Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on PyMC3 v3.9.0\n"
     ]
    }
   ],
   "source": [
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pymc3 as pm\n",
    "\n",
    "print(f\"Running on PyMC3 v{pm.__version__}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'retina'\n",
    "az.style.use(\"arviz-darkgrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This model replicates the example used in:\n",
    "Kruschke, John. (2012) **Bayesian estimation supersedes the t-test**. *Journal of Experimental Psychology*: General."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Problem\n",
    "\n",
    "Several statistical inference procedures involve the comparison of two groups. We may be interested in whether one group is larger than another, or simply different from the other. We require a statistical model for this because true differences are usually accompanied by measurement or stochastic noise that prevent us from drawing conclusions simply from differences calculated from the observed data. \n",
    "\n",
    "The *de facto* standard for statistically comparing two (or more) samples is to use a statistical test. This involves expressing a null hypothesis, which typically claims that there is no difference between the groups, and using a chosen test statistic to determine whether the distribution of the observed data is plausible under the hypothesis. This rejection occurs when the calculated test statistic is higher than some pre-specified threshold value.\n",
    "\n",
    "Unfortunately, it is not easy to conduct hypothesis tests correctly, and their results are very easy to misinterpret. Setting up a statistical test involves several subjective choices (*e.g.* statistical test to use, null hypothesis to test, significance level) by the user that are rarely justified based on the problem or decision at hand, but rather, are usually based on traditional choices that are entirely arbitrary (Johnson 1999). The evidence that it provides to the user is indirect, incomplete, and typically overstates the evidence against the null hypothesis (Goodman 1999). \n",
    "\n",
    "A more informative and effective approach for comparing groups is one based on **estimation** rather than **testing**, and is driven by Bayesian probability rather than frequentist. That is, rather than testing whether two groups are different, we instead pursue an estimate of how different they are, which is fundamentally more informative. Moreover, we include an estimate of uncertainty associated with that difference which includes uncertainty due to our lack of knowledge of the model parameters (epistemic uncertainty) and uncertainty due to the inherent stochasticity of the system (aleatory uncertainty)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Drug trial evaluation\n",
    "\n",
    "To illustrate how this Bayesian estimation approach works in practice, we will use a fictitious example from Kruschke (2012) concerning the evaluation of a clinical trial for drug evaluation. The trial aims to evaluate the efficacy of a \"smart drug\" that is supposed to increase intelligence by comparing IQ scores of individuals in a treatment arm (those receiving the drug) to those in a control arm (those recieving a placebo). There are 47 individuals and 42 individuals in the treatment and control arms, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 387,
       "width": 1009
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fmt: off\n",
    "drug = (101,100,102,104,102,97,105,105,98,101,100,123,105,103,100,95,102,106,\n",
    "        109,102,82,102,100,102,102,101,102,102,103,103,97,97,103,101,97,104,\n",
    "        96,103,124,101,101,100,101,101,104,100,101)\n",
    "placebo = (99,101,100,101,102,100,97,101,104,101,102,102,100,105,88,101,100,\n",
    "           104,100,100,100,101,102,103,97,101,101,100,101,99,101,100,100,\n",
    "           101,100,99,101,100,102,99,100,99)\n",
    "# fmt: on\n",
    "\n",
    "y1 = np.array(drug)\n",
    "y2 = np.array(placebo)\n",
    "y = pd.DataFrame(\n",
    "    dict(value=np.r_[y1, y2], group=np.r_[[\"drug\"] * len(drug), [\"placebo\"] * len(placebo)])\n",
    ")\n",
    "\n",
    "y.hist(\"value\", by=\"group\", figsize=(12, 4));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first step in a Bayesian approach to inference is to specify the full probability model that corresponds to the problem. For this example, Kruschke chooses a Student-t distribution to describe the distributions of the scores in each group. This choice adds robustness to the analysis, as a T distribution is less sensitive to outlier observations, relative to a normal distribution. The three-parameter Student-t distribution allows for the specification of a mean $\\mu$, a precision (inverse-variance) $\\lambda$ and a degrees-of-freedom parameter $\\nu$:\n",
    "\n",
    "$$f(x|\\mu,\\lambda,\\nu) = \\frac{\\Gamma(\\frac{\\nu + 1}{2})}{\\Gamma(\\frac{\\nu}{2})} \\left(\\frac{\\lambda}{\\pi\\nu}\\right)^{\\frac{1}{2}} \\left[1+\\frac{\\lambda(x-\\mu)^2}{\\nu}\\right]^{-\\frac{\\nu+1}{2}}$$\n",
    "           \n",
    "the degrees-of-freedom parameter essentially specifies the \"normality\" of the data, since larger values of $\\nu$ make the distribution converge to a normal distribution, while small values (close to zero) result in heavier tails.\n",
    "\n",
    "Thus, the likelihood functions of our model are specified as follows:\n",
    "\n",
    "$$y^{(treat)}_i \\sim T(\\nu, \\mu_1, \\sigma_1)$$\n",
    "\n",
    "$$y^{(placebo)}_i \\sim T(\\nu, \\mu_2, \\sigma_2)$$\n",
    "\n",
    "As a simplifying assumption, we will assume that the degree of normality $\\nu$ is the same for both groups. We will, of course, have separate parameters for the means $\\mu_k, k=1,2$ and standard deviations $\\sigma_k$.\n",
    "\n",
    "Since the means are real-valued, we will apply normal priors on them, and arbitrarily set the hyperparameters to the pooled empirical mean of the data and twice the pooled empirical standard deviation, which applies very diffuse information to these quantities (and importantly, does not favor one or the other *a priori*).\n",
    "\n",
    "$$\\mu_k \\sim N(\\bar{x}, 2s)$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "μ_m = y.value.mean()\n",
    "μ_s = y.value.std() * 2\n",
    "\n",
    "with pm.Model() as model:\n",
    "    group1_mean = pm.Normal(\"group1_mean\", mu=μ_m, sd=μ_s)\n",
    "    group2_mean = pm.Normal(\"group2_mean\", mu=μ_m, sd=μ_s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The group standard deviations will be given a uniform prior over a plausible range of values for the variability of the outcome variable, IQ.\n",
    "\n",
    "In Kruschke's original model, he uses a very wide uniform prior for the group standard deviations, from the pooled empirical standard deviation divided by 1000 to the pooled standard deviation multiplied by 1000. This is a poor choice of prior, because very basic prior knowledge about measures of human coginition dictate that the variation cannot ever be as high as this upper bound. IQ is a standardized measure, and hence this constrains how variable a given population's IQ values can be. When you place such a wide uniform prior on these values, you are essentially giving a lot of prior weight on inadmissable values. In this example, there is little practical difference, but in general it is best to apply as much prior information that you have available to the parameterization of prior distributions. \n",
    "\n",
    "We will instead set the group standard deviations to have a $\\text{Uniform}(1,10)$ prior:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "σ_low = 1\n",
    "σ_high = 10\n",
    "\n",
    "with model:\n",
    "    group1_std = pm.Uniform(\"group1_std\", lower=σ_low, upper=σ_high)\n",
    "    group2_std = pm.Uniform(\"group2_std\", lower=σ_low, upper=σ_high)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We follow Kruschke by making the prior for $\\nu$ exponentially distributed with a mean of 30; this allocates high prior probability over the regions of the parameter that describe the range from normal to heavy-tailed data under the Student-T distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 409,
       "width": 638
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "with model:\n",
    "    ν = pm.Exponential(\"ν_minus_one\", 1 / 29.0) + 1\n",
    "\n",
    "pm.kdeplot(np.random.exponential(30, size=10000), fill_kwargs={\"alpha\": 0.5});"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since PyMC3 parameterizes the Student-T in terms of precision, rather than standard deviation, we must transform the standard deviations before specifying our likelihoods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "with model:\n",
    "    λ1 = group1_std ** -2\n",
    "    λ2 = group2_std ** -2\n",
    "\n",
    "    group1 = pm.StudentT(\"drug\", nu=ν, mu=group1_mean, lam=λ1, observed=y1)\n",
    "    group2 = pm.StudentT(\"placebo\", nu=ν, mu=group2_mean, lam=λ2, observed=y2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Having fully specified our probabilistic model, we can turn our attention to calculating the comparisons of interest in order to evaluate the effect of the drug. To this end, we can specify deterministic nodes in our model for the difference between the group means and the difference between the group standard deviations. Wrapping them in named `Deterministic` objects signals to PyMC that we wish to record the sampled values as part of the output.\n",
    "\n",
    "As a joint measure of the groups, we will also estimate the \"effect size\", which is the difference in means scaled by the pooled estimates of standard deviation. This quantity can be harder to interpret, since it is no longer in the same units as our data, but the quantity is a function of all four estimated parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "with model:\n",
    "    diff_of_means = pm.Deterministic(\"difference of means\", group1_mean - group2_mean)\n",
    "    diff_of_stds = pm.Deterministic(\"difference of stds\", group1_std - group2_std)\n",
    "    effect_size = pm.Deterministic(\n",
    "        \"effect size\", diff_of_means / np.sqrt((group1_std ** 2 + group2_std ** 2) / 2)\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we can fit the model and evaluate its output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [ν_minus_one, group2_std, group1_std, group2_mean, group1_mean]\n"
     ]
    },
    {
     "data": {
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       "                border: none;\n",
       "                /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "                background-size: auto;\n",
       "            }\n",
       "            .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "                background: #F44336;\n",
       "            }\n",
       "        </style>\n",
       "      <progress value='12000' class='' max='12000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [12000/12000 00:06<00:00 Sampling 4 chains, 0 divergences]\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 1_000 tune and 2_000 draw iterations (4_000 + 8_000 draws total) took 10 seconds.\n"
     ]
    }
   ],
   "source": [
    "with model:\n",
    "    trace = pm.sample(2000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can plot the stochastic parameters of the model. PyMC's `plot_posterior` function replicates the informative histograms portrayed in Kruschke (2012). These summarize the posterior distributions of the parameters, and present a 95% credible interval and the posterior mean. The plots below are constructed with the final 1000 samples from each of the 2 chains, pooled together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/dependencies/arviz/arviz/data/io_pymc3.py:89: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n",
      "  FutureWarning,\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2484x1104 with 6 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1115,
       "width": 2495
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.plot_posterior(\n",
    "    trace,\n",
    "    var_names=[\"group1_mean\", \"group2_mean\", \"group1_std\", \"group2_std\", \"ν_minus_one\"],\n",
    "    color=\"#87ceeb\",\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the group differences below, we can conclude that there are meaningful differences between the two groups for all three measures. For these comparisons, it is useful to use zero as a reference value (`ref_val`); providing this reference value yields cumulative probabilities for the posterior distribution on either side of the value. Thus, for the difference of means, at least 97% of the posterior probability are greater than zero, which suggests the group means are credibly different. The effect size and differences in standard deviation are similarly positive.\n",
    "\n",
    "These estimates suggest that the \"smart drug\" increased both the expected scores, but also the variability in scores across the sample. So, this does not rule out the possibility that some recipients may be adversely affected by the drug at the same time others benefit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/dependencies/arviz/arviz/data/io_pymc3.py:89: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n",
      "  FutureWarning,\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2484x552 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 563,
       "width": 2495
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.plot_posterior(\n",
    "    trace,\n",
    "    var_names=[\"difference of means\", \"difference of stds\", \"effect size\"],\n",
    "    ref_val=0,\n",
    "    color=\"#87ceeb\",\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When `forestplot` is called on a trace with more than one chain, it also plots the potential scale reduction parameter, which is used to reveal evidence for lack of convergence; values near one, as we have here, suggest that the model has converged."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/dependencies/arviz/arviz/data/io_pymc3.py:89: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n",
      "  FutureWarning,\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 600x580 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 591,
       "width": 611
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.forestplot(trace, var_names=[\"group1_mean\", \"group2_mean\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/dependencies/arviz/arviz/data/io_pymc3.py:89: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n",
      "  FutureWarning,\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 731,
       "width": 611
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.forestplot(trace, var_names=[\"group1_std\", \"group2_std\", \"ν_minus_one\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/dependencies/pymc3/pymc3/stats/__init__.py:35: UserWarning: Keyword argument `varnames` renamed to `var_names`, and will be removed in pymc3 3.9\n",
      "  \"pymc3 3.9\".format(old=old, new=new)\n",
      "/dependencies/arviz/arviz/data/io_pymc3.py:89: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n",
      "  FutureWarning,\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>hdi_3%</th>\n",
       "      <th>hdi_97%</th>\n",
       "      <th>mcse_mean</th>\n",
       "      <th>mcse_sd</th>\n",
       "      <th>ess_mean</th>\n",
       "      <th>ess_sd</th>\n",
       "      <th>ess_bulk</th>\n",
       "      <th>ess_tail</th>\n",
       "      <th>r_hat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>difference of means</th>\n",
       "      <td>1.015</td>\n",
       "      <td>0.438</td>\n",
       "      <td>0.184</td>\n",
       "      <td>1.827</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.005</td>\n",
       "      <td>4880.0</td>\n",
       "      <td>4639.0</td>\n",
       "      <td>4894.0</td>\n",
       "      <td>4809.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>difference of stds</th>\n",
       "      <td>0.927</td>\n",
       "      <td>0.454</td>\n",
       "      <td>0.180</td>\n",
       "      <td>1.858</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.005</td>\n",
       "      <td>4998.0</td>\n",
       "      <td>4998.0</td>\n",
       "      <td>4829.0</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>effect size</th>\n",
       "      <td>0.606</td>\n",
       "      <td>0.276</td>\n",
       "      <td>0.091</td>\n",
       "      <td>1.130</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.003</td>\n",
       "      <td>5008.0</td>\n",
       "      <td>5008.0</td>\n",
       "      <td>4981.0</td>\n",
       "      <td>5112.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  \\\n",
       "difference of means  1.015  0.438   0.184    1.827      0.006    0.005   \n",
       "difference of stds   0.927  0.454   0.180    1.858      0.006    0.005   \n",
       "effect size          0.606  0.276   0.091    1.130      0.004    0.003   \n",
       "\n",
       "                     ess_mean  ess_sd  ess_bulk  ess_tail  r_hat  \n",
       "difference of means    4880.0  4639.0    4894.0    4809.0    1.0  \n",
       "difference of stds     4998.0  4998.0    4829.0    3715.0    1.0  \n",
       "effect size            5008.0  5008.0    4981.0    5112.0    1.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm.summary(trace, varnames=[\"difference of means\", \"difference of stds\", \"effect size\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "1.\tGoodman SN. Toward evidence-based medical statistics. 1: The P value fallacy. Annals of Internal Medicine. 1999;130(12):995-1004. doi:10.7326/0003-4819-130-12-199906150-00008.\n",
    "2.\tJohnson D. The insignificance of statistical significance testing. Journal of Wildlife Management. 1999;63(3):763-772.\n",
    "3.\tKruschke JK. Bayesian estimation supersedes the t test. J Exp Psychol Gen. 2013;142(2):573-603. doi:10.1037/a0029146."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The original pymc2 implementation was written by Andrew Straw and can be found here: https://github.com/strawlab/best\n",
    "\n",
    "Ported to PyMC3 by [Thomas Wiecki](https://twitter.com/twiecki) (c) 2015, updated by Chris Fonnesbeck."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pymc3  3.9.0\n",
      "numpy  1.18.5\n",
      "arviz  0.8.3\n",
      "pandas 1.0.4\n",
      "last updated: Mon Jun 15 2020 \n",
      "\n",
      "CPython 3.7.7\n",
      "IPython 7.15.0\n",
      "watermark 2.0.2\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -n -u -v -iv -w"
   ]
  }
 ],
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  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  },
  "latex_envs": {
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 0
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 },
 "nbformat": 4,
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}