{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Разведочный анализ утомленных лекцией\n",
"\n",
"Пример анализа данных, полученных в рамках проектной деятельности с помощью онлайн-приложения \"[Баланс внимания](http://balatte.stireac.com/)\".\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"tags": [
"remove-cell"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"%pylab inline\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"\n",
"import scipy.stats as stats\n",
"import statsmodels.api as sm\n",
"smf = sm.formula\n",
"from statsmodels.stats.anova import anova_lm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Методика\n",
"\n",
"1-й этап эксперимента:\n",
"-\tПодготовка испытуемого и настрой на проведение контрольного теста. - 10 минут\n",
"-\tКонтрольный тест баланса внимания #1. - 5 минут - Тест в обычных условиях без физических и умственных нагрузок\n",
"-\tОтдых. - 7 минут\n",
"\n",
"2-й этап эксперимента:\n",
"-\tВоздействие на испытуемого умственной нагрузкой, понижающей мотивацию, в виде просмотра видеозаписи лекции на сложную и непонятную испытуемым тему ( лекция теории Марковских случайных процессов https://www.youtube.com/watch?v=UveMw1SjEM4 ) - 15 минут. \n",
"Контроль внимательности просмотра видео обеспечивается путем подсчета количества произношения разных форм слова \"процесс\". (Например: процессом, процесса и т.д.) \n",
"-\tТест баланса внимания #2. - 5 минут \n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
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864 rows × 8 columns
\n",
"
"
],
"text/plain": [
" t v isi g mod subj cond nagr10\n",
"0 9.537 0.332 NaN 8.0 v 0 0 NaN\n",
"1 17.354 0.243 7.817 8.0 v 0 0 1.0\n",
"2 25.094 0.238 7.740 8.0 v 0 0 2.0\n",
"3 32.211 0.298 7.117 8.0 v 0 0 2.0\n",
"4 39.839 0.253 7.628 8.0 v 0 0 2.0\n",
".. ... ... ... ... .. ... ... ...\n",
"859 232.453 0.361 2.322 2.0 a 9 lect 4.0\n",
"860 234.724 0.298 2.271 2.0 a 9 lect 5.0\n",
"861 236.662 0.304 1.938 2.0 a 9 lect 5.0\n",
"862 239.017 0.309 2.355 2.0 a 9 lect 5.0\n",
"863 240.979 0.290 1.962 2.0 a 9 lect 5.0\n",
"\n",
"[864 rows x 8 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"D = pd.read_table('d/rt9x2.tsv')\n",
"D"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- t время предъявления стимула, с\n",
"- v время реакции, с\n",
"- isi межстимульный интервал (МСИ), с\n",
"- g режим стимуляции. В ходе тестирования МСИ задавался с небольшой вариацией в окрестности трех значений: 8, 4, 2 с.\n",
"8 - субъективно медленно, 4 - комфортно, 2 - часто.\n",
"Функциональное состояние изменялось от монотонии до активации\n",
"- mod модальность стимула visual - зрительный audial - слуховой\n",
"- subj идентификатор участника\n",
"- cond условие тестирования 0 - контроль, lect - после лекции\n",
"- nagr10 - \"текущая нагрузка\" - количество стимулов, требующих реакции, за последние 10 с.\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Проверка полноты выборки необходима, чтобы при всех сочетаниях факторов объём данных был достаточным для статистики.\n",
"Проверка полноты выполняется путем подсчета значений в каждой группе."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"subj cond mod\n",
"0 0 a 24\n",
" v 24\n",
" lect a 24\n",
" v 22\n",
"1 0 a 24\n",
" v 23\n",
" lect a 24\n",
" v 21\n",
"3 0 a 24\n",
" v 24\n",
" lect a 24\n",
" v 24\n",
"4 0 a 24\n",
" v 23\n",
" lect a 24\n",
" v 24\n",
"5 0 a 24\n",
" v 23\n",
" lect a 24\n",
" v 23\n",
"6 0 a 24\n",
" v 21\n",
" lect a 24\n",
" v 24\n",
"7 0 a 24\n",
" v 23\n",
" lect a 19\n",
" v 24\n",
"8 0 a 24\n",
" v 24\n",
" lect a 24\n",
" v 20\n",
"9 0 a 23\n",
" v 24\n",
" lect a 24\n",
" v 24\n",
"Name: v, dtype: int64"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"D.groupby(['subj','cond','mod']).v.count()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"При группировке по нескольким колонкам на выходе получаем серию значений (pd.Series) со сложным индексом. У каждого значения в серии несколько указателей - по одному из каждой группирующей колонки.\n",
"По первому индексу `subj` понятно, что в тесте приняли участие 9 субъектов (респондентов).\n",
"В норме в каждой группе по 24 значения, но если были пропуски (значения отсутствуют), то в группе оказывается меньше значений.\n",
"\n",
"Так как серия с количеством значений была на выходе последней команды, то к ней можно обратиться через специальное имя `_` (подчерк). Например, узнать в какой группе было больше всего пропусков, и, соответственно, меньше всего числовых значений."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"26"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"_.argmin()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Строка в таблице для значения может быть, а само значение в этой строке отсутствовать.\n",
"В этом случае обычно на его месте ставят NaN (Not a Number)."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"23"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"D.v.isnull().sum()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Во всем наборе данных 23 пустых значения."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(864, 8)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"D.shape"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"864"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"24 * 2 * 2 * 9 # n * mod * cond * subj"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Таким образом, в таблице есть строчки для всех сочетаний факторов, но из-за пропусков реальных значений меньше. Анализ полноты повторных измерений (repeated measures) показал, что для каждого сочетания факторов было не менее 19 повторов."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Анализ распределения зависимой переменной\n",
"\n",
"Зависимая переменная `v` - ВР, с.\n",
"\n",
"Перед тем, как применять методы параметрической статистики нужно убедиться, что значения варьируют близко к нормальному распределению."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.histplot(D.v.dropna(), kde=True, element=\"step\", label='Плотность');\n",
"axvline(D.v.median(),c='r',ls='--', label='Медиана');\n",
"xlabel('ВР, с')\n",
"ylabel('%')\n",
"legend();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Распределение имеет четко выраженную центральную тенденцию - один \"горб\" посередине и плавно убывающие \"хвосты\" по бокам.\n",
"Левый фронт более крутой - распределение асимметрично со сдвигом вправо. \n",
"Для введения в модель степени асимметричности нужен еще один параметр, однако такое усложнение потребует специальных методов статистического анализа.\n",
"В данном случае выгоднее пренебречь небольшим отклонением от нормальности в виде асимметрии, но при этом воспользоваться хорошо разработанным математическим аппаратом вариационной статистики."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Чтобы не влияли редкие значения, попавшие в хвосты распределения, \"обрежем\" его в тех границах, где плотность подходит к нулю."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"X = D[(D.v>=.18)&(D.v<.72)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"В этом распределены смешаны данные, полученные при разных условиях и модальности стимулов. Сопоставим групповые выборки с помощью разных типов графиков."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.catplot(x='cond', y='v', hue='mod', data=X, kind='violin');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Вариационный анализ"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Семейство статистических методов, оценивающих возможности объяснить дисперсию (вариацию) в целевом (зависимом) показателе за счет вариации объясняющих (независимых) показателей, называют дисперсионный анализ или анализ вариации. \n",
"В названии конкретных методов часто встречается аббревиатура ANOVA (ANalysis Of VAriation). Основы дисперсионного анализа были разработаны Р. Фишером.\n",
"\n",
"При записи формулы многофакторных моделей объясняющие факторы записывают как части суммы, а если еще учитывают их совместное (сочетанное) действие, то как множители произведения.\n",
"\n",
"$$v \\sim Cond*Mod$$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"В процессе анализа основное внимание сосредоточим на действии фактора \"условие\" (cond), при этом разделяя реакции на стимулы разных модальностей (mod) - зрительные и слуховые, - потому что зрительное и слуховое внимание работают на основе разных механизмов."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Проведем многофакторный вариационный анализ для повторных измерений с помощью пакета statmodels.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\a\\winpython\\python-3.9.0rc1.amd64\\lib\\site-packages\\statsmodels\\regression\\mixed_linear_model.py:2237: ConvergenceWarning: The MLE may be on the boundary of the parameter space.\n",
" warnings.warn(msg, ConvergenceWarning)\n"
]
},
{
"data": {
"text/html": [
"
\n",
"
\n",
"
Model:
MixedLM
Dependent Variable:
v
\n",
"
\n",
"
\n",
"
No. Observations:
824
Method:
REML
\n",
"
\n",
"
\n",
"
No. Groups:
9
Scale:
0.0045
\n",
"
\n",
"
\n",
"
Min. group size:
88
Log-Likelihood:
1023.8836
\n",
"
\n",
"
\n",
"
Max. group size:
95
Converged:
Yes
\n",
"
\n",
"
\n",
"
Mean group size:
91.6
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
Coef.
Std.Err.
z
P>|z|
[0.025
0.975]
\n",
"
\n",
"
\n",
"
Intercept
0.339
0.022
15.444
0.000
0.296
0.382
\n",
"
\n",
"
\n",
"
cond[T.lect]
0.002
0.007
0.316
0.752
-0.011
0.015
\n",
"
\n",
"
\n",
"
mod[T.v]
-0.009
0.007
-1.305
0.192
-0.021
0.004
\n",
"
\n",
"
\n",
"
cond[T.lect]:mod[T.v]
0.011
0.009
1.143
0.253
-0.008
0.029
\n",
"
\n",
"
\n",
"
subj Var
0.004
0.031
\n",
"
\n",
"
"
],
"text/plain": [
"\n",
"\"\"\"\n",
" Mixed Linear Model Regression Results\n",
"================================================================\n",
"Model: MixedLM Dependent Variable: v \n",
"No. Observations: 824 Method: REML \n",
"No. Groups: 9 Scale: 0.0045 \n",
"Min. group size: 88 Log-Likelihood: 1023.8836\n",
"Max. group size: 95 Converged: Yes \n",
"Mean group size: 91.6 \n",
"----------------------------------------------------------------\n",
" Coef. Std.Err. z P>|z| [0.025 0.975]\n",
"----------------------------------------------------------------\n",
"Intercept 0.339 0.022 15.444 0.000 0.296 0.382\n",
"cond[T.lect] 0.002 0.007 0.316 0.752 -0.011 0.015\n",
"mod[T.v] -0.009 0.007 -1.305 0.192 -0.021 0.004\n",
"cond[T.lect]:mod[T.v] 0.011 0.009 1.143 0.253 -0.008 0.029\n",
"subj Var 0.004 0.031 \n",
"================================================================\n",
"\n",
"\"\"\""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mo = smf.mixedlm('v ~ cond*mod', data=X, groups='subj').fit()\n",
"mo.summary()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Значения ВР в с слишком маленькие, и алгоритм подбора параметров модели выдает предупреждение о сходимости (ConvergenceWarning).\n",
"\n",
"Попробуем перевести значения в мс и запустим еще раз.\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"
\n",
"
Model:
MixedLM
Dependent Variable:
rtms
\n",
"
\n",
"
\n",
"
No. Observations:
824
Method:
REML
\n",
"
\n",
"
\n",
"
No. Groups:
9
Scale:
4496.2534
\n",
"
\n",
"
\n",
"
Min. group size:
88
Log-Likelihood:
-4640.4757
\n",
"
\n",
"
\n",
"
Max. group size:
95
Converged:
Yes
\n",
"
\n",
"
\n",
"
Mean group size:
91.6
\n",
"
\n",
"
\n",
"
\n",
"
\n",
"
Coef.
Std.Err.
z
P>|z|
[0.025
0.975]
\n",
"
\n",
"
\n",
"
Intercept
338.706
21.932
15.444
0.000
295.721
381.691
\n",
"
\n",
"
\n",
"
cond[T.lect]
2.075
6.563
0.316
0.752
-10.789
14.938
\n",
"
\n",
"
\n",
"
mod[T.v]
-8.560
6.562
-1.305
0.192
-21.421
4.300
\n",
"
\n",
"
\n",
"
cond[T.lect]:mod[T.v]
10.693
9.352
1.143
0.253
-7.636
29.021
\n",
"
\n",
"
\n",
"
subj Var
4138.924
31.394
\n",
"
\n",
"
"
],
"text/plain": [
"\n",
"\"\"\"\n",
" Mixed Linear Model Regression Results\n",
"====================================================================\n",
"Model: MixedLM Dependent Variable: rtms \n",
"No. Observations: 824 Method: REML \n",
"No. Groups: 9 Scale: 4496.2534 \n",
"Min. group size: 88 Log-Likelihood: -4640.4757\n",
"Max. group size: 95 Converged: Yes \n",
"Mean group size: 91.6 \n",
"--------------------------------------------------------------------\n",
" Coef. Std.Err. z P>|z| [0.025 0.975]\n",
"--------------------------------------------------------------------\n",
"Intercept 338.706 21.932 15.444 0.000 295.721 381.691\n",
"cond[T.lect] 2.075 6.563 0.316 0.752 -10.789 14.938\n",
"mod[T.v] -8.560 6.562 -1.305 0.192 -21.421 4.300\n",
"cond[T.lect]:mod[T.v] 10.693 9.352 1.143 0.253 -7.636 29.021\n",
"subj Var 4138.924 31.394 \n",
"====================================================================\n",
"\n",
"\"\"\""
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"D['rtms'] = D.v * 1000\n",
"X = D[(D.v>=.18)&(D.v<.72)]\n",
"mo = smf.mixedlm('rtms ~ cond*mod', data=X, groups='subj').fit()\n",
"mo.summary()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"В таблице результатов надо смотреть колонку `P>|z|` - это и есть p-value, вероятность того, что влияние факторов случайно. Действие фактора расценивается существенным, если p-значение меньше 0.05.\n",
"\n",
"Если не учитывать ритм подачи стимулов, то различия не обнаруживаются."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Распределения с учетом МСИ\n",
"\n",
"Если мы хотим сопоставить на одном рисунке несколько распределений, то вместо классических гистограмм, которые будут закрывать друг друга при наложении, можно использовать графики оценки плотности ядра (KDE - kernel density estimation).\n",
"\n",
"График оценки плотности ядра (KDE) - это метод визуализации\n",
"распределения наблюдений в наборе данных, аналогичный гистограмме. KDE\n",
"представляет данные с использованием непрерывной кривой плотности вероятности."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"g_lw = {2:3, 4:1.5, 8:0.8}\n",
"co_cond = {'0':'green', 'lect':'crimson'}\n",
"\n",
"fig,ax = subplots(1,2, sharey=True, figsize=(12,6))\n",
"\n",
"for i,modality in enumerate(['v','a']):\n",
" sca(ax[i])\n",
" title(modality)\n",
" \n",
" g=D[D['mod']==modality].groupby(['cond','g'])\n",
" for k in sorted(g.groups.keys()):\n",
" vv = g.get_group(k).v.dropna()\n",
" cond,gr = k\n",
" sns.kdeplot(vv, label=k, color=co_cond[cond], lw=g_lw[gr]);\n",
" xlabel('ВР, с')\n",
" ylabel('%')\n",
" legend();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Фактор `g` - группа влияет достоверно, но как именно? \n",
"И у всех ли испытуемых однонаправленно?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Анализ на R\n",
"\n",
"Статистики исторически любят работать в среде языка R, поэтому самые свежие версии алгоритмов анализа могут быть доступны в виде библиотек на R.\n",
"Если на компьютере установлен бесплатный пакет R, то тут же в блокноте можно провести анализ.\n",
"Для этого надо загрузить расширение для подключения R.\n",
"```\n",
"%load_ext rpy2.ipython\n",
"```\n",
"\n",
"После этого, если ячейка начинается со специальной команды `%%R`, то код в ней обрабатывается не в Python, а в R. Например, импорт библиотек на языке R осуществляется командой library, а не import.\n",
"```\n",
"%%R \n",
"library(car)\n",
"library(lme4)\n",
"```\n",
"\n",
"Для анализа нужно передать в среду R наш набор данных, который мы указываем после ключа `-i` - input вход.\n",
"```py\n",
"%%R -i X\n",
"\n",
"(m1 <- lmer(v ~ cond*mod*g + (1|subj), data = X))\n",
"Anova(m1, test.statistic=\"F\")\n",
"```\n",
"\n",
"На выходе получаем результат в виде текста:\n",
"```\n",
"Analysis of Deviance Table (Type II Wald F tests with Kenward-Roger df)\n",
"\n",
"Response: v\n",
" F Df Df.res Pr(>F) \n",
"cond 2.5504 1 808.01 0.1107 \n",
"mod 0.5121 1 808.03 0.4745 \n",
"g 19.7105 1 808.02 1.026e-05 ***\n",
"cond:mod 1.5166 1 808.02 0.2185 \n",
"cond:g 1.8920 1 808.01 0.1694 \n",
"mod:g 0.6344 1 808.01 0.4260 \n",
"cond:mod:g 0.4963 1 808.02 0.4813 \n",
"---\n",
"Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Значимость влияния фактора в результатах анализа помечены кодами - звёздочками. Чем больше звездочек, тем больше значимость."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Сопоставив средние ВР для трех МСИ, мы можем понять, что ВР при увеличении МСИ растет. В данном случае взаимодействие фактора `g` с другими не выявлено.\n",
"\n",
"Чтобы оценить форму зависимости при разных сочетаниях уровней факторов, выведем график зависимости для каждого респондента."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"h = sns.catplot(x='g', y='v', hue='subj', col='cond', row='mod', data=X, \n",
" kind='point', alpha=0.5);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"На одном рисунке мы визуализировали зависимости ВР от МСИ для каждой группы модальности/условия/испытуемого.\n"
]
}
],
"metadata": {
"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": "3.9.0rc1"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": false,
"sideBar": false,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 4
}