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Merge pull request #338 from coding-for-reproducible-research/accessibility_iframe
Modifications for WCAG 2.2
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‎R_functions/quiz_renderer.R

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# quiz_renderer.R
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# Load required libraries
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library(jsonlite)
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library(IRdisplay)
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library(uuid) # For generating unique quiz IDs
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show_quiz_from_json <- function(path, quiz_id_prefix = NULL) {
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quiz_data <- fromJSON(path, simplifyVector = FALSE)
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# Generate a unique prefix if one isn't supplied
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if (is.null(quiz_id_prefix)) {
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quiz_id_prefix <- paste0("quiz_", UUIDgenerate(use.time = TRUE))
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}
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html <- '
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<style>
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.quiz-question {
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background-color: #392061;
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color: white;
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padding: 12px;
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border-radius: 10px;
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font-weight: bold;
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font-size: 1.2em;
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margin-bottom: 10px;
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}
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.quiz-form {
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margin-bottom: 20px;
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}
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.quiz-answer {
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display: block;
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background-color: #f2f2f2;
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border: none;
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border-radius: 10px;
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padding: 10px;
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margin: 5px 0;
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font-size: 1em;
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cursor: pointer;
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text-align: left;
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transition: background-color 0.3s;
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width: 100%;
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}
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.quiz-answer:hover {
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background-color: #e0e0e0;
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}
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.correct {
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background-color: #4CAF50 !important;
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color: white !important;
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border: none;
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}
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.incorrect {
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background-color: #D32F2F !important;
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color: white !important;
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border: none;
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}
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.feedback {
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margin-top: 10px;
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font-weight: bold;
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font-size: 1em;
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}
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</style>
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<script>
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function handleAnswer(qid, aid, feedback, isCorrect) {
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let buttons = document.querySelectorAll("." + qid);
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buttons.forEach(btn => {
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btn.classList.remove("correct", "incorrect");
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});
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let selected = document.getElementById(aid);
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if (selected) {
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selected.classList.add(isCorrect ? "correct" : "incorrect");
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}
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let feedbackBox = document.getElementById("feedback_" + qid);
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if (feedbackBox) {
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feedbackBox.innerHTML = feedback;
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feedbackBox.style.color = isCorrect ? "green" : "red";
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}
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}
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</script>
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'
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for (i in seq_along(quiz_data)) {
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question <- quiz_data[[i]]
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qid <- sprintf("%s_q%s", quiz_id_prefix, i)
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html <- paste0(html, sprintf('<div class="quiz-question">%s</div><form class="quiz-form">', question$question))
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for (j in seq_along(question$answers)) {
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answer <- question$answers[[j]]
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aid <- sprintf("%s_a%s", qid, j)
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feedback <- gsub("'", "\\'", answer$feedback)
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correct <- tolower(substr(answer$feedback, 1, 7)) == "correct"
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correct_js <- tolower(as.character(correct))
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html <- paste0(html, sprintf(
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'<button type="button" class="quiz-answer %s" id="%s"
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onclick="handleAnswer(\'%s\', \'%s\', \'%s\', %s)">
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%s</button>',
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qid, aid, qid, aid, feedback, correct_js, answer$answer
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))
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}
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html <- paste0(html, sprintf(
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'<div class="feedback" id="feedback_%s"></div>
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<button type="submit" style="position:absolute; left:-9999px; width:1px; height:1px; overflow:hidden;">
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Submit
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</button>
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</form><hr>', qid))
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}
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display_html(html)
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}

‎individual_modules/advanced_regression_analysis_with_R/advanced_regression_analysis_with_R_extras.ipynb

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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 1,
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"id": "3bd18871-f159-4905-b82f-df059bc416a3",
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"metadata": {
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"editable": true,
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 2,
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"id": "4a078d31-2ae4-4215-affe-111c49a4059f",
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"metadata": {
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"editable": true,
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"Call:\n",
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"lm(formula = CognitionB ~ VisitNum * Sex, data = cogDat)\n",
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"\n",
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"Residuals:\n",
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" Min 1Q Median 3Q Max \n",
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"-12.937 -2.827 0.218 2.982 12.064 \n",
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"\n",
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"Coefficients:\n",
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" Estimate Std. Error t value Pr(>|t|) \n",
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"(Intercept) 7.7202 0.4353 17.737 < 2e-16 ***\n",
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"VisitNum 0.3977 0.1196 3.325 0.000931 ***\n",
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"SexM 1.2563 0.6497 1.934 0.053556 . \n",
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"VisitNum:SexM -0.4590 0.1858 -2.471 0.013729 * \n",
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"---\n",
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"Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
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"\n",
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"Residual standard error: 4.527 on 693 degrees of freedom\n",
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"Multiple R-squared: 0.01617,\tAdjusted R-squared: 0.01192 \n",
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"F-statistic: 3.798 on 3 and 693 DF, p-value: 0.01017\n",
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"\n"
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]
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"data": {
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"text/plain": [
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"\n",
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"Call:\n",
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"lm(formula = CognitionB ~ VisitNum * Sex, data = cogDat)\n",
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"\n",
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"Residuals:\n",
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" Min 1Q Median 3Q Max \n",
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"-11.465 -3.117 0.125 2.918 14.382 \n",
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"\n",
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"Coefficients:\n",
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" Estimate Std. Error t value Pr(>|t|) \n",
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"(Intercept) 9.2834 0.5080 18.275 <2e-16 ***\n",
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"VisitNum -0.1923 0.1564 -1.230 0.219 \n",
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"SexM -0.6392 0.6616 -0.966 0.334 \n",
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"VisitNum:SexM -0.0136 0.1999 -0.068 0.946 \n",
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"---\n",
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"Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
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"\n",
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"Residual standard error: 4.262 on 668 degrees of freedom\n",
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"Multiple R-squared: 0.01283,\tAdjusted R-squared: 0.008394 \n",
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"F-statistic: 2.893 on 3 and 668 DF, p-value: 0.03462\n"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 3,
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"id": "4fa1e36f-894a-4b4a-82d8-62a3849ff5a8",
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"metadata": {
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"editable": true,
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"Call:\n",
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"lm(formula = CognitionB ~ VisitNum:Sex, data = cogDat)\n",
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"\n",
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"Residuals:\n",
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" Min 1Q Median 3Q Max \n",
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"-12.7225 -2.9448 0.2117 3.0424 11.6298 \n",
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"\n",
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"Coefficients:\n",
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" Estimate Std. Error t value Pr(>|t|) \n",
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"(Intercept) 8.28413 0.32378 25.585 < 2e-16 ***\n",
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"VisitNum:SexF 0.26797 0.09922 2.701 0.00709 ** \n",
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"VisitNum:SexM 0.11395 0.10974 1.038 0.29946 \n",
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"---\n",
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"Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
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"\n",
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"Residual standard error: 4.536 on 694 degrees of freedom\n",
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"Multiple R-squared: 0.01087,\tAdjusted R-squared: 0.008016 \n",
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"F-statistic: 3.812 on 2 and 694 DF, p-value: 0.02257\n",
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"\n"
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]
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"data": {
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"text/plain": [
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"\n",
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"Call:\n",
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"lm(formula = CognitionB ~ VisitNum:Sex, data = cogDat)\n",
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"\n",
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"Residuals:\n",
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" Min 1Q Median 3Q Max \n",
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"-11.5941 -3.1624 0.1885 2.9499 14.5579 \n",
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"\n",
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"Coefficients:\n",
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" Estimate Std. Error t value Pr(>|t|) \n",
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"(Intercept) 8.90655 0.32541 27.370 < 2e-16 ***\n",
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"VisitNum:SexF -0.09198 0.11687 -0.787 0.43155 \n",
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"VisitNum:SexM -0.27235 0.10386 -2.622 0.00894 ** \n",
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"---\n",
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"Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
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"\n",
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"Residual standard error: 4.262 on 669 degrees of freedom\n",
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"Multiple R-squared: 0.01145,\tAdjusted R-squared: 0.008493 \n",
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"F-statistic: 3.874 on 2 and 669 DF, p-value: 0.02125\n"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 4,
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"id": "ca2c5012-a2c2-4e7e-ac5b-75ffcfec49ae",
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"metadata": {
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"editable": true,
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"Call:\n",
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"lm(formula = CognitionB ~ Sex + VisitNum:Sex, data = cogDat)\n",
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"\n",
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"Residuals:\n",
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" Min 1Q Median 3Q Max \n",
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"-12.937 -2.827 0.218 2.982 12.064 \n",
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"\n",
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"Coefficients:\n",
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" Estimate Std. Error t value Pr(>|t|) \n",
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"(Intercept) 7.72023 0.43527 17.737 < 2e-16 ***\n",
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"SexM 1.25633 0.64970 1.934 0.053556 . \n",
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"SexF:VisitNum 0.39774 0.11962 3.325 0.000931 ***\n",
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"SexM:VisitNum -0.06122 0.14213 -0.431 0.666781 \n",
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"---\n",
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"Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
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"\n",
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"Residual standard error: 4.527 on 693 degrees of freedom\n",
235-
"Multiple R-squared: 0.01617,\tAdjusted R-squared: 0.01192 \n",
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"F-statistic: 3.798 on 3 and 693 DF, p-value: 0.01017\n",
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"\n"
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]
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"data": {
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"text/plain": [
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"\n",
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"Call:\n",
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"lm(formula = CognitionB ~ Sex + VisitNum:Sex, data = cogDat)\n",
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"\n",
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"Residuals:\n",
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" Min 1Q Median 3Q Max \n",
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"-11.465 -3.117 0.125 2.918 14.382 \n",
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"\n",
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"Coefficients:\n",
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" Estimate Std. Error t value Pr(>|t|) \n",
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"(Intercept) 9.2834 0.5080 18.275 <2e-16 ***\n",
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"SexM -0.6392 0.6616 -0.966 0.3343 \n",
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"SexF:VisitNum -0.1923 0.1564 -1.230 0.2191 \n",
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"SexM:VisitNum -0.2059 0.1245 -1.654 0.0987 . \n",
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"---\n",
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"Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
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"\n",
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"Residual standard error: 4.262 on 668 degrees of freedom\n",
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"Multiple R-squared: 0.01283,\tAdjusted R-squared: 0.008394 \n",
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"F-statistic: 2.893 on 3 and 668 DF, p-value: 0.03462\n"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [

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