{ "cells": [ { "cell_type": "markdown", "id": "56ce9f7f-a824-4f54-966a-64d6fcc2be3d", "metadata": {}, "source": [ "# Effect size (Cohen's d)\n", "\n", "The first ingredient in a power analysis is **effect size**. \n", "\n", "Power analysis determines the sample size needed to detect an effect of a certain size.\n", "\n", "What is **effect size**? It is a measure of whether the effect (difference of means, correlation) of interest is big or small, *relative to the random noise or variability in the data*.\n", "\n", "In this notebook we look at the effect size for the $t$-test and for Pearson's correlation. We will see that:\n", "\n", "* The effect size for the $t$-test is Cohen's $d$, where\n", "\n", "$$ d = \\frac{\\bar{x_1}-\\bar{x_2}}{s} $$\n", "\n", "* The effect size for Pearson's correlation is simply the correlation coefficient, $r$\n", "\n", "## Video\n", "\n", "Here is a video explaining the idea of effect size for:\n", "* difference of means (Cohen's $d$)\n", "* correlation (Spearman's $r$)" ] }, { "cell_type": "code", "execution_count": 1, "id": "6ac9fd69-83a4-452a-bf05-5648081c42ae", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%%HTML\n", "" ] }, { "cell_type": "markdown", "id": "963b0c5c-faa7-4fe0-b498-a72443e4c681", "metadata": {}, "source": [ "### Set up Python libraries\n", "\n", "As usual, run the code cell below to import the relevant Python libraries" ] }, { "cell_type": "code", "execution_count": 3, "id": "c4b005e8-fa09-46ab-a67f-5be8eef52546", "metadata": { "tags": [] }, "outputs": [], "source": [ "# Set-up Python libraries - you need to run this but you don't need to change it\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import scipy.stats as stats\n", "import pandas as pd\n", "import seaborn as sns\n", "sns.set_theme(style='white')\n", "import statsmodels.api as sm\n", "import statsmodels.formula.api as smf\n", "import warnings \n", "warnings.simplefilter('ignore', category=FutureWarning)" ] }, { "cell_type": "markdown", "id": "2e61e927-cbf1-4dae-bf36-7151494bae71", "metadata": {}, "source": [ "## Effect size for the $t$-test\n", "\n", "**Example:**\n", "\n", "A researcher hypothesises that geography students are taller than psychology students.\n", "\n", "$\\mathcal{H_o}:$ The mean heights of psychology ($\\mu_p$) and geography ($\\mu_g$) students are the same; $\\mu_p = \\mu_g$\n", "\n", "$\\mathcal{H_a}:$ The mean heights of geography students is greater than the mean height of psychology students; $\\mu_g > \\mu_p$\n", "\n", "\n", "He measures the heights of 12 geography students an 10 psychology students, which are given in the dataframe below:" ] }, { "cell_type": "code", "execution_count": 4, "id": "11bf9185-8f0e-45e4-943f-f99e97ac6ef8", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
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studentIDsubjectheight
0186640psychology154.0
1588140psychology156.3
2977390psychology165.6
3948470psychology162.0
4564360psychology162.0
5604180psychology159.0
6770760psychology166.1
7559170psychology165.9
8213240psychology163.7
9660220psychology165.6
10311550psychology163.1
11249170psychology176.6
12139690geography171.6
13636160geography171.5
14649650geography154.6
15595280geography162.6
16772880geography164.4
17174880geography168.6
18767580geography175.3
19688870geography168.4
20723650geography183.5
21445960geography164.1
\n", "
" ], "text/plain": [ " studentID subject height\n", "0 186640 psychology 154.0\n", "1 588140 psychology 156.3\n", "2 977390 psychology 165.6\n", "3 948470 psychology 162.0\n", "4 564360 psychology 162.0\n", "5 604180 psychology 159.0\n", "6 770760 psychology 166.1\n", "7 559170 psychology 165.9\n", "8 213240 psychology 163.7\n", "9 660220 psychology 165.6\n", "10 311550 psychology 163.1\n", "11 249170 psychology 176.6\n", "12 139690 geography 171.6\n", "13 636160 geography 171.5\n", "14 649650 geography 154.6\n", "15 595280 geography 162.6\n", "16 772880 geography 164.4\n", "17 174880 geography 168.6\n", "18 767580 geography 175.3\n", "19 688870 geography 168.4\n", "20 723650 geography 183.5\n", "21 445960 geography 164.1" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "heights=pd.read_csv('https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook_2024/main/data/PsyGeogHeights.csv')\n", "heights" ] }, { "cell_type": "markdown", "id": "98f1bb0e-5adf-42f4-8d0d-b2ca90e54409", "metadata": {}, "source": [ "Let's calculate the sample mean for each subject group:" ] }, { "cell_type": "code", "execution_count": 2, "id": "16ac5cc1", "metadata": { "tags": [] }, "outputs": [ { "ename": "NameError", "evalue": "name 'heights' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mheights\u001b[49m\u001b[38;5;241m.\u001b[39mgroupby(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msubject\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;241m.\u001b[39mheight\u001b[38;5;241m.\u001b[39mmean()\n", "\u001b[0;31mNameError\u001b[0m: name 'heights' is not defined" ] } ], "source": [ "heights.groupby('subject').height.mean()" ] }, { "cell_type": "markdown", "id": "02bb074f-99c8-4ac4-bc3d-a37b3f59b6a2", "metadata": {}, "source": [ "So the Geography students are about 5cm taller than the Psychology students.\n", "\n", "Is this a large difference? Would it be obvious in a psychology-geography student party who is a psychology student and who is a geography student, just from their heights? \n", "\n", "We can visualise how much the populations overlap by plotting them:" ] }, { "cell_type": "code", "execution_count": 73, "id": "3316dce1", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot KDEs\n", "sns.kdeplot(data=heights, x='height', hue='subject', fill=True)\n", "sns.rugplot(data=heights, x='height', hue='subject', height=0.1)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "a3a8dc1b-e192-407d-ac06-a06e3a58a08b", "metadata": {}, "source": [ "Hm, no, we probably could not tell who is a psychology student and who is a geography student, just from their heights, but it looks like there is a difference between the groups overall." ] }, { "cell_type": "markdown", "id": "bccbdec7-1c17-488d-bc29-cf924b8b89ca", "metadata": {}, "source": [ "### Effect size $\\neq$ statistical significance \n", "\n", "We could ask if there is a statistically signifiant difference between the groups by running a $t$-test:" ] }, { "cell_type": "code", "execution_count": 74, "id": "49b5733f-107c-4c57-ac7b-68e688e9f933", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Ttest_indResult(statistic=1.7743564827449236, pvalue=0.04561467878556142)" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "stats.ttest_ind(heights.query('subject==\"geography\"').height,\n", " heights.query('subject==\"psychology\"').height, \n", " alternative='greater')" ] }, { "cell_type": "markdown", "id": "ff1241fe-5e42-48f3-aeaa-80ef0cfe0ebe", "metadata": {}, "source": [ "The difference is *just* significant at $\\alpha$=0.05 - our $p$-value is 0.0456\n", "\n", "**However**, this doesn't really tell us whether the effect is big (whether we could easily spot a tall geography student at a Psychosoc party), because the value of $t$ also depends on the sample size, $n$. To illustrate this, consider the following sample `heights2`, which is ten times larger (120 psychology students and 100 geography students), but with the same mean and sd in each group as the small ($n$ = 12,10) sample:" ] }, { "cell_type": "code", "execution_count": 75, "id": "67885d43-3a6b-4789-849e-5a7a7e288de3", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "heights2 = pd.read_csv('https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook_2024/main/data/heightsLargerSample.csv')\n", "\n", "plt.figure(figsize=(8,4))\n", "plt.subplot(1,2,1)\n", "plt.title('$n$=10,12')\n", "sns.kdeplot(data=heights, x='height', hue='subject', fill=True)\n", "sns.rugplot(data=heights, x='height', hue='subject', height=0.1)\n", "\n", "plt.subplot(1,2,2)\n", "plt.title('$n$=100,120')\n", "sns.kdeplot(data=heights2, x='height', hue='subject', fill=True)\n", "sns.rugplot(data=heights2, x='height', hue='subject', height=0.1)\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "d23f9d61-4ead-4b2f-b40c-7bcfe1fa8e48", "metadata": { "tags": [] }, "source": [ "Although the mean and sd for each group are about the same, if we conduct a $t$-test on the larger dataset, we find the difference is *much* more significant" ] }, { "cell_type": "code", "execution_count": 76, "id": "74804c61-8b15-42f4-99db-46bc91e78516", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Ttest_indResult(statistic=1.7743564827449236, pvalue=0.04561467878556142)" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# small sample size\n", "stats.ttest_ind(heights.query('subject==\"geography\"').height,\n", " heights.query('subject==\"psychology\"').height, \n", " alternative='greater')" ] }, { "cell_type": "code", "execution_count": 77, "id": "d0523eab-bf59-4d3a-a012-4e65aba31cab", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Ttest_indResult(statistic=4.770032273659233, pvalue=1.6851503676180654e-06)" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# large sample size\n", "stats.ttest_ind(heights2.query('subject==\"geography\"').height,\n", " heights2.query('subject==\"psychology\"').height, \n", " alternative='greater')" ] }, { "cell_type": "markdown", "id": "b7b8a6af-e6b1-4cab-8d4c-f971fe9db722", "metadata": {}, "source": [ "**Conclusion** the $t$-test cannot tell us whether the effect of subject studied on height is large or small - for this we need a 'pure' measure of the size of the difference relative to variability, regardless of $n$" ] }, { "cell_type": "markdown", "id": "7522b1cf-bd06-464f-992c-b411e9ca0ba2", "metadata": {}, "source": [ "## Variance matters for effect size\n", "\n", "Is a 5cm difference in height between psychology and geography students a big effect? How easily could we spot a tall geographer gatecrashing the Psychosoc party?\n", "\n", "This will depend on both the difference in mean heights, and the standard deviation (variablity) within each group.\n", "\n", "Consider the following dataset which has the same difference in means, but now much less variability within each group:" ] }, { "cell_type": "code", "execution_count": 78, "id": "ff06235c-df85-4c56-a5e3-90bdca7b9e50", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "heights3 = pd.read_csv('https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook_2024/main/data/heightsSmallerSD.csv')\n", "\n", "plt.figure(figsize=(8,4))\n", "# plot KDEs\n", "plt.subplot(1,2,1)\n", "plt.title('larger sd')\n", "sns.kdeplot(data=heights, x='height', hue='subject', fill=True)\n", "sns.rugplot(data=heights, x='height', hue='subject', height=0.1)\n", "plt.xlim([150,175])\n", "\n", "plt.subplot(1,2,2)\n", "plt.title('smaller sd')\n", "sns.kdeplot(data=heights3, x='height', hue='subject', fill=True)\n", "sns.rugplot(data=heights3, x='height', hue='subject', height=0.1)\n", "plt.xlim([150,175])\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "0e789d5e-4001-431b-8653-28dbe0ea9eba", "metadata": {}, "source": [ "For the dataset on the right (lower sd within each group) we can see a much clearer separation between the psychology and geography students - in practical terms, it would be easier to guess a person's subject based on their height.\n", "\n", "The plot on the right has a **larger effect size**, as we shall see in the next section" ] }, { "cell_type": "markdown", "id": "9da61f73-fc4b-4b41-8275-278f13dd657a", "metadata": {}, "source": [ "## Cohen's $d$\n", "\n", "We quantify the effect size for the difference of means as Cohen's $d$:\n", "\n", "$$ d = \\frac{\\bar{x_g}-\\bar{x_p}}{s} $$\n", "\n", "where:\n", "* $\\bar{x_g}$ is the mean height of our sample of geography students\n", "* $\\bar{x_p}$ is the mean height of our sample of psychology students\n", "* $s$ is the *shared standard deviation estimate* basaed on the standard deviations of the samples, $s_p$ and $s_g$:\n", "\n", "$$ s = \\sqrt{\\frac{(n_p-1)s_p^2 + (n_g-1)s_g^2)}{n_p + n_g - 2}} $$" ] }, { "cell_type": "markdown", "id": "ae1499b9-5ca4-47f0-991a-8ef8833a2ee6", "metadata": {}, "source": [ "oof! The *shared variance (or sd) estimate*, $s$, is just a way of getting a single 'average' standard deviation measure when we have two sample standard deviations for our two groups, and is actually part of the equation from the independent samples $t$-test.\n", "\n", "$$t = \\frac{\\bar{x_1}-\\bar{x_2}}{s\\sqrt{\\frac{1}{n_1}+\\frac{1}{n_2}}}$$\n", "\n", "Let's implement that:" ] }, { "cell_type": "code", "execution_count": 80, "id": "75b4edbb", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "6.758944074335872" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# calculate shared standard deviation s\n", "\n", "xP = heights.query('subject==\"psychology\"').height.mean()\n", "xG = heights.query('subject==\"geography\"').height.mean()\n", "\n", "sP = heights.query('subject==\"psychology\"').height.std()\n", "sG = heights.query('subject==\"geography\"').height.std()\n", "\n", "nP = heights.query('subject==\"psychology\"').height.count()\n", "nG = heights.query('subject==\"geography\"').height.count()\n", "\n", "s=(((nP-1)*(sP**2) + (nG-1)*(sG**2))/(nP+nG-2))**0.5 # **0.5 means 'to the power of a half' ie square root\n", "s" ] }, { "cell_type": "markdown", "id": "6310b74d-d82e-4df3-8b13-97dd65b539b1", "metadata": {}, "source": [ "$s$ is an estimate of the standard deviation of heights, based on both groups, so it should be similar to the standard deviation of each of the individual groups." ] }, { "cell_type": "markdown", "id": "8248b7be-7ddd-4b0e-ba6a-724300b6d0bb", "metadata": {}, "source": [ "Now we can calculate our effect size:" ] }, { "cell_type": "code", "execution_count": 35, "id": "2350aef1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.7597340566106963" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Cohen's d\n", "d=(xG-xP)/s\n", "d" ] }, { "cell_type": "markdown", "id": "82e31d5e-384e-492e-b39d-1fb706ee36e0", "metadata": {}, "source": [ "So $d=0.76$, ie the difference in mean heights between psychology and geography students is 0.76 standard deviations.\n", "\n", "### Effect size is a *standardized* measure\n", "\n", "Note that in dividing the difference by the standard deviations, we are quantifying the overlap between the two distributions **independent of the data values themselves.**\n", "\n", "Therefore it is possible to have quite different datasets with the same effect size - for example if the difference of means and the standard deviations both increase, effect size may stay the same.\n", "\n", "For example, here I have created another dataset with the same effect size $d=0.760$, comparing the weights of (fictional) black and grey sheep:" ] }, { "cell_type": "code", "execution_count": 25, "id": "a46d52c9", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sheep=pd.read_csv('https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook_2024/main/data/SheepWeights.csv')\n", "\n", "# plot KDEs for psy/geog heights\n", "plt.subplot(2,1,1)\n", "sns.kdeplot(data=heights, x='height', hue='subject', fill=True)\n", "plt.xlabel('student height (cm)')\n", "plt.xlim([50,300])\n", "plt.ylim([0,0.04])\n", "\n", "# plot KDEs for black/grey sheep weights\n", "plt.subplot(2,1,2)\n", "sns.kdeplot(data=sheep, x='weight', hue='woolColor', fill=True)\n", "plt.xlabel('sheep weight (lb)')\n", "plt.xlim([50,300])\n", "plt.ylim([0,0.04])\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "122a346a-1e88-45d5-9843-32ded19152d0", "metadata": {}, "source": [ "Although the 'sheep' data are much more spread out, the difference of means between groups is also larger. \n", "\n", "These two different datasets therefore have the same effect size, which quantifies the *overlap* between groups (psychology and geography students, or black and grey sheep)" ] }, { "cell_type": "markdown", "id": "5eab9f74-bba1-4357-b815-700a4c6a591a", "metadata": { "tags": [] }, "source": [ "### Small, medium and large effects\n", "\n", "Cohen himself defined small medium and large effects as follows:\n", "\n", "* $d=0.2$: small effect\n", "* $d=0.5$: medium effect\n", "* $d=0.8$: large effect\n", "\n", "stating that *\"a medium effect of 0.5 is visible to the naked eye of a careful observer\"*\n", "\n", "This is what the effect sizes look like for normally distributed data:\n", " \n", "\n" ] }, { "cell_type": "markdown", "id": "30d47799-15d3-48d6-a4f7-aa304bf22189", "metadata": {}, "source": [ "Of course, even tiny differences are \"visible to the naked eye\" for these smooth curves; in contrast, for real data, there will be uncertainty about how well some fitted curve (KDE plot) really represents the underlying population - hence to ascertain our confidence in the difference (statistical significance), we must consider the sample size $n$ as well as effect size." ] }, { "cell_type": "markdown", "id": "f777218d-3d79-49eb-ab1a-478e81e88520", "metadata": {}, "source": [ "## Recovering $d$ from $t$\n", "\n", "Most published papers do not report effect sizes or Cohen's $d$ for $t$-tests\n", "\n", "However, they do report $t$ values and sample sizes. \n", "\n", "$d$ can be recovered relatively simply from $t$ and $n$ - the formulae for this (for the paired and unpaired t-test) are given in the page **Determining effect size**\n", "\n", "This is important as we often need to use the effect size from a published study to *estimate* the effect size in a study we are planning, and thus select the correct sample size via power analysis. This process will be explored later in this chapter." ] }, { "cell_type": "code", "execution_count": null, "id": "4df32c48-81a4-4e5f-a318-8813ec64dad3", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.7" } }, "nbformat": 4, "nbformat_minor": 5 }