-
Notifications
You must be signed in to change notification settings - Fork 0
/
3_stan_brms_long2.html
533 lines (460 loc) · 20 KB
/
3_stan_brms_long2.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8" />
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />
<title>3_stan_brms_long2.utf8.md</title>
<script src="site_libs/jquery-1.11.3/jquery.min.js"></script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link href="site_libs/bootstrap-3.3.5/css/bootstrap.min.css" rel="stylesheet" />
<script src="site_libs/bootstrap-3.3.5/js/bootstrap.min.js"></script>
<script src="site_libs/bootstrap-3.3.5/shim/html5shiv.min.js"></script>
<script src="site_libs/bootstrap-3.3.5/shim/respond.min.js"></script>
<script src="site_libs/navigation-1.1/tabsets.js"></script>
<link href="site_libs/highlightjs-9.12.0/default.css" rel="stylesheet" />
<script src="site_libs/highlightjs-9.12.0/highlight.js"></script>
<style type="text/css">code{white-space: pre;}</style>
<style type="text/css">
pre:not([class]) {
background-color: white;
}
</style>
<script type="text/javascript">
if (window.hljs) {
hljs.configure({languages: []});
hljs.initHighlightingOnLoad();
if (document.readyState && document.readyState === "complete") {
window.setTimeout(function() { hljs.initHighlighting(); }, 0);
}
}
</script>
<style type="text/css">
h1 {
font-size: 34px;
}
h1.title {
font-size: 38px;
}
h2 {
font-size: 30px;
}
h3 {
font-size: 24px;
}
h4 {
font-size: 18px;
}
h5 {
font-size: 16px;
}
h6 {
font-size: 12px;
}
.table th:not([align]) {
text-align: left;
}
</style>
</head>
<body>
<style type = "text/css">
.main-container {
max-width: 940px;
margin-left: auto;
margin-right: auto;
}
code {
color: inherit;
background-color: rgba(0, 0, 0, 0.04);
}
img {
max-width:100%;
height: auto;
}
.tabbed-pane {
padding-top: 12px;
}
.html-widget {
margin-bottom: 20px;
}
button.code-folding-btn:focus {
outline: none;
}
summary {
display: list-item;
}
</style>
<style type="text/css">
/* padding for bootstrap navbar */
body {
padding-top: 51px;
padding-bottom: 40px;
}
/* offset scroll position for anchor links (for fixed navbar) */
.section h1 {
padding-top: 56px;
margin-top: -56px;
}
.section h2 {
padding-top: 56px;
margin-top: -56px;
}
.section h3 {
padding-top: 56px;
margin-top: -56px;
}
.section h4 {
padding-top: 56px;
margin-top: -56px;
}
.section h5 {
padding-top: 56px;
margin-top: -56px;
}
.section h6 {
padding-top: 56px;
margin-top: -56px;
}
.dropdown-submenu {
position: relative;
}
.dropdown-submenu>.dropdown-menu {
top: 0;
left: 100%;
margin-top: -6px;
margin-left: -1px;
border-radius: 0 6px 6px 6px;
}
.dropdown-submenu:hover>.dropdown-menu {
display: block;
}
.dropdown-submenu>a:after {
display: block;
content: " ";
float: right;
width: 0;
height: 0;
border-color: transparent;
border-style: solid;
border-width: 5px 0 5px 5px;
border-left-color: #cccccc;
margin-top: 5px;
margin-right: -10px;
}
.dropdown-submenu:hover>a:after {
border-left-color: #ffffff;
}
.dropdown-submenu.pull-left {
float: none;
}
.dropdown-submenu.pull-left>.dropdown-menu {
left: -100%;
margin-left: 10px;
border-radius: 6px 0 6px 6px;
}
</style>
<script>
// manage active state of menu based on current page
$(document).ready(function () {
// active menu anchor
href = window.location.pathname
href = href.substr(href.lastIndexOf('/') + 1)
if (href === "")
href = "index.html";
var menuAnchor = $('a[href="' + href + '"]');
// mark it active
menuAnchor.parent().addClass('active');
// if it's got a parent navbar menu mark it active as well
menuAnchor.closest('li.dropdown').addClass('active');
});
</script>
<div class="container-fluid main-container">
<!-- tabsets -->
<style type="text/css">
.tabset-dropdown > .nav-tabs {
display: inline-table;
max-height: 500px;
min-height: 44px;
overflow-y: auto;
background: white;
border: 1px solid #ddd;
border-radius: 4px;
}
.tabset-dropdown > .nav-tabs > li.active:before {
content: "";
font-family: 'Glyphicons Halflings';
display: inline-block;
padding: 10px;
border-right: 1px solid #ddd;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
content: "";
border: none;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open:before {
content: "";
font-family: 'Glyphicons Halflings';
display: inline-block;
padding: 10px;
border-right: 1px solid #ddd;
}
.tabset-dropdown > .nav-tabs > li.active {
display: block;
}
.tabset-dropdown > .nav-tabs > li > a,
.tabset-dropdown > .nav-tabs > li > a:focus,
.tabset-dropdown > .nav-tabs > li > a:hover {
border: none;
display: inline-block;
border-radius: 4px;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open > li {
display: block;
float: none;
}
.tabset-dropdown > .nav-tabs > li {
display: none;
}
</style>
<script>
$(document).ready(function () {
window.buildTabsets("TOC");
});
$(document).ready(function () {
$('.tabset-dropdown > .nav-tabs > li').click(function () {
$(this).parent().toggleClass('nav-tabs-open')
});
});
</script>
<!-- code folding -->
<div class="navbar navbar-default navbar-fixed-top" role="navigation">
<div class="container">
<div class="navbar-header">
<button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar">
<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</button>
<a class="navbar-brand" href="index.html">Fertility diary</a>
</div>
<div id="navbar" class="navbar-collapse collapse">
<ul class="nav navbar-nav">
<li>
<a href="1_power_analysis.html">Power analysis</a>
</li>
<li>
<a href="1_researcher_df_analysis.html">Researcher degree of freedom simulation</a>
</li>
<li>
<a href="1_wrangle_data.html">Data wrangling</a>
</li>
<li>
<a href="2_descriptives.html">Descriptives</a>
</li>
<li>
<a href="3_fertility_as_prereg.html">Preregistered analyses</a>
</li>
<li>
<a href="3_fertility_robustness.html">Robustness tests</a>
</li>
</ul>
<ul class="nav navbar-nav navbar-right">
</ul>
</div><!--/.nav-collapse -->
</div><!--/.container -->
</div><!--/.navbar -->
<div class="fluid-row" id="header">
</div>
<div id="item-level-model-for-extra-pair-items" class="section level1 tab-content">
<h1>Item-level model for extra-pair items</h1>
<p><span style="background:red;width:20px;height:20px;display:inline-block;"></span> Cycling women (not on hormonal birth control)</p>
<p><span style="background:black;width:20px;height:20px;display:inline-block;"></span> Women on hormonal birth control</p>
<div id="load-data" class="section level2">
<h2>Load data</h2>
<pre class="r"><code>library(knitr)
opts_chunk$set(fig.width = 12, fig.height = 12, cache = F, warning = F, message = F)</code></pre>
<pre class="r"><code>library(formr); library(data.table); library(stringr); library(ggplot2); library(plyr); library(dplyr);library(car); library(psych);
source("0_helpers.R")
library(brms)
load("full_data.rdata")
diary$included = diary$included_all
diary_long = diary %>% group_by(person) %>%
filter(!is.na(included_all), !is.na(fertile_fab)) %>%
mutate(included = included_all,
fertile = fertile_fab,
fertile_mean = mean(fertile_fab, na.rm = T)) %>%
select(person, menstruation, RCD_inferred, fertile_mean, fertile, fertile_fab, included, extra_pair_2, extra_pair_3, extra_pair_4, extra_pair_5, extra_pair_6, extra_pair_7, extra_pair_8, extra_pair_9, extra_pair_10, extra_pair_11, extra_pair_12, extra_pair_13) %>%
tidyr::gather(variable, value, -person, -menstruation, -fertile_mean,-fertile, -fertile_fab, -included, -RCD_inferred)
items = readxl::read_xlsx("item_tables/Daily_items_bearbeitetAM.xlsx", 1) %>% rename(`Item.name` = `Item name`)
diary_long = diary_long %>% left_join(items %>% select(Item.name, Item), by = c("variable" = "Item.name"))</code></pre>
<p>Dan Engber helpfully pointed out that he inferred from the plot caption in the manuscript, that the curves reflected shapes standardised across hormonal contraceptive users and non-users. In fact, each curve shown was standardised within group, because we wanted to draw the eye to the differences in <em>changes</em>, not in mean levels. This leads to an inconsistency with the other graph by group, where mean levels play a role too. Unfortunately, we did not explain this inconsistency in the text. Here, I show the same graph, but standardised only by item and not within the groups of HC users and non-users. We still see what looks like “post-menstrual catch-up” in in-pair sexual desire for hormonal contraceptive users. Importantly, the pattern we see for non-hormonal contraceptive users may also include some such post-menstrual catch-up (although it’s less visible against the background of ovulatory change). So as not to confuse such non-ovulatory cyclical changes (which may be behaviorally driven rather than hormonally) with those related to ovulation, we used the hormonal contraceptive users as quasi-control group.</p>
</div>
<div id="item-level-raw-means-over-cycle-days" class="section level2">
<h2>Item-level raw means over cycle days</h2>
<pre class="r"><code>theme_henrik <- function(grid=TRUE, legend.position=NA) {
th <- ggplot2::theme_minimal(base_size = 12)
th <- th + theme(text = element_text(color='#333333'))
th <- th + theme(legend.background = element_blank())
th <- th + theme(legend.key = element_blank())
# Straight out of hrbrthemes
if (inherits(grid, "character") | grid == TRUE) {
th <- th + theme(panel.grid=element_line(color="#cccccc", size=0.3))
th <- th + theme(panel.grid.major=element_line(color="#cccccc", size=0.3))
th <- th + theme(panel.grid.minor=element_line(color="#cccccc", size=0.15))
if (inherits(grid, "character")) {
if (regexpr("X", grid)[1] < 0) th <- th + theme(panel.grid.major.x=element_blank())
if (regexpr("Y", grid)[1] < 0) th <- th + theme(panel.grid.major.y=element_blank())
if (regexpr("x", grid)[1] < 0) th <- th + theme(panel.grid.minor.x=element_blank())
if (regexpr("y", grid)[1] < 0) th <- th + theme(panel.grid.minor.y=element_blank())
}
} else {
th <- th + theme(panel.grid=element_blank())
}
th <- th + theme(axis.text = element_text())
th <- th + theme(axis.ticks = element_blank())
th <- th + theme(axis.text.x=element_text(margin=margin(t=0.5)))
th <- th + theme(axis.text.y=element_text(margin=margin(r=0.5)))
th <- th + theme(plot.title = element_text(),
plot.subtitle = element_text(margin=margin(b=15)),
plot.caption = element_text(face='italic', size=10))
if (!is.na(legend.position)) th <- th + theme(legend.position = legend.position)
return (th)
}
diary %>% group_by(person) %>%
filter(!is.na(fertile_fab), !is.na(included_all),
RCD > -1 * minimum_cycle_length_diary, RCD > -29) %>%
filter(!is.na(included_all), !is.na(fertile_fab)) %>%
mutate(included = included_all,
fertile_mean = mean(fertile_fab, na.rm = T)) %>%
select(person, n_days, menstruation, RCD_inferred, fertile_mean, fertile_fab, included, extra_pair_2, extra_pair_3, extra_pair_4, extra_pair_5, extra_pair_6, extra_pair_7, extra_pair_8, extra_pair_9, extra_pair_10, extra_pair_11, extra_pair_12, extra_pair_13, desirability_partner, desirability_1, sexual_intercourse_1, attention_2
# ,extra_pair, in_pair_desire
) %>%
tidyr::gather(variable, value, -person, -menstruation, -fertile_mean, -fertile_fab, -included, -RCD_inferred, -n_days) %>%
left_join(items %>% select(Item.name, Item), by = c("variable" = "Item.name")) %>%
mutate(RCD_inferred = -1* RCD_inferred + 1, variable = factor(str_wrap(str_sub(Item,4),40))) %>%
filter(!is.na(value), RCD_inferred > -29) %>%
group_by(included, person, variable) %>%
mutate(value = value - min(value),
value = value / max(value)) %>%
group_by(included, Item, variable, RCD_inferred) %>%
summarise(value = mean(value, na.rm = T)) %>%
group_by(included, variable) %>%
arrange(RCD_inferred) %>%
mutate(
value_min = value - min(value),
p_peak = value_min / max(value_min), # Normalize as percentage of peak popularity
p_smooth = (
coalesce(lag(p_peak), p_peak[RCD_inferred==0]) + p_peak + coalesce(lead(p_peak), p_peak[RCD_inferred==-28])) / 3 # Moving average, accounting for cyclical nature
) %>% # When there's no lag or lead, we get NA. Use the pointwise data
group_by(included) %>%
mutate(variable = reorder(variable, p_smooth, FUN=which.max)) %>% # order by peak time
arrange(variable) %>%
mutate(variable.f = reorder(as.character(variable), desc(variable))) ->
item_timeseries</code></pre>
<pre class="r"><code>ts_plot = item_timeseries %>%
filter(!is.na(included)) %>%
{
items <- levels(.$variable)
ggplot(., aes(x = RCD_inferred, group = variable.f, fill = factor(paste0(included,as.integer(variable.f) %% 2)))) +
geom_ribbon(aes(ymin = as.integer(variable), ymax = as.integer(variable) + 2 * (p_smooth)), color='white', size=0.4) +
scale_x_continuous("Days until next menstruation", breaks = c(-0,-7,-14,-21,-28), labels = c("0","7","14","21","28")) +
# "Re-add" activities by names as labels in the Y scale
scale_y_continuous(breaks = 1:length(items) + 0.4, labels = function(y) {items[y]})+
# Zebra color for readability; will change colors of labels in Inkscape later
scale_fill_manual(values = c('horm_contra0' = '#444444', 'horm_contra1' = '#222222', 'cycling0' = '#F13B0E', 'cycling1' = '#B7320E'))+
ggtitle("") +
theme_henrik(grid='', legend.position='none') +
theme(
axis.ticks.x = element_line(size=0.3),
axis.ticks.y = element_line(size=0.3),
axis.text.y = element_text(size = 10))+
facet_wrap(~ included, labeller = labeller(included = c(`cycling` = 'Naturally cycling', `horm_contra` = 'Hormonal contraceptive user'))) +
geom_segment(aes(x = if_else(included=="cycling",-14,NA_real_), xend = if_else(included=="cycling",-14,NA_real_)), color = 'darkred', linetype = 'dashed', y = 0.7, yend = 17.7)+
geom_text(data = data.frame(included = 'cycling', variable.f = 1, RCD_inferred = -14), label = 'est. day of ovulation', color = 'darkred', y = 0.5)
}
ggsave(ts_plot, file = "item_timeseries.pdf", width = 10, height = 10)
ts_plot</code></pre>
<p><img src="3_stan_brms_long2_files/figure-html/unnamed-chunk-2-1.png" width="1152" /></p>
</div>
<div id="item-level-raw-means-over-cycle-days-modified" class="section level2">
<h2>Item-level raw means over cycle days (modified)</h2>
<pre class="r"><code>diary %>% group_by(person) %>%
filter(!is.na(fertile_fab), !is.na(included_all),
RCD > -1 * minimum_cycle_length_diary, RCD > -29) %>%
filter(!is.na(included_all), !is.na(fertile_fab)) %>%
mutate(included = included_all,
fertile_mean = mean(fertile_fab, na.rm = T)) %>%
select(person, n_days, menstruation, RCD_inferred, fertile_mean, fertile_fab, included, extra_pair_2, extra_pair_3, extra_pair_4, extra_pair_5, extra_pair_6, extra_pair_7, extra_pair_8, extra_pair_9, extra_pair_10, extra_pair_11, extra_pair_12, extra_pair_13, desirability_partner, desirability_1, sexual_intercourse_1, attention_2
# ,extra_pair, in_pair_desire
) %>%
tidyr::gather(variable, value, -person, -menstruation, -fertile_mean, -fertile_fab, -included, -RCD_inferred, -n_days) %>%
left_join(items %>% select(Item.name, Item), by = c("variable" = "Item.name")) %>%
mutate(RCD_inferred = -1* RCD_inferred + 1, variable = factor(str_wrap(str_sub(Item,4),40))) %>%
filter(!is.na(value), RCD_inferred > -29) %>%
group_by(included, person, variable) %>%
mutate(value = value - min(value),
value = value / max(value)) %>%
group_by(included, Item, variable, RCD_inferred) %>%
summarise(value = mean(value, na.rm = T)) %>%
group_by(variable) %>%
arrange(RCD_inferred) %>%
mutate(
value_min = value - min(value),
p_peak = value_min / max(value_min)) %>%
group_by(included, variable) %>% # Normalize as percentage of peak popularity
mutate(
p_smooth = (
coalesce(lag(p_peak), p_peak[RCD_inferred==0]) + p_peak + coalesce(lead(p_peak), p_peak[RCD_inferred==-28])) / 3 # Moving average, accounting for cyclical nature
) %>% # When there's no lag or lead, we get NA. Use the pointwise data
group_by(included) %>%
mutate(variable = reorder(variable, p_smooth, FUN=which.max)) %>% # order by peak time
arrange(variable) %>%
mutate(variable.f = reorder(as.character(variable), desc(variable))) ->
item_timeseries</code></pre>
<pre class="r"><code>ts_plot = item_timeseries %>%
filter(!is.na(included)) %>%
{
items <- levels(.$variable)
ggplot(., aes(x = RCD_inferred, group = variable.f, fill = factor(paste0(included,as.integer(variable.f) %% 2)))) +
geom_ribbon(aes(ymin = as.integer(variable), ymax = as.integer(variable) + 2 * (p_smooth)), color='white', size=0.4) +
scale_x_continuous("Days until next menstruation", breaks = c(-0,-7,-14,-21,-28), labels = c("0","7","14","21","28")) +
# "Re-add" activities by names as labels in the Y scale
scale_y_continuous(breaks = 1:length(items) + 0.4, labels = function(y) {items[y]})+
# Zebra color for readability; will change colors of labels in Inkscape later
scale_fill_manual(values = c('horm_contra0' = '#444444', 'horm_contra1' = '#222222', 'cycling0' = '#F13B0E', 'cycling1' = '#B7320E'))+
ggtitle("") +
theme_henrik(grid='', legend.position='none') +
theme(
axis.ticks.x = element_line(size=0.3),
axis.ticks.y = element_line(size=0.3),
axis.text.y = element_text(size = 10))+
facet_wrap(~ included, labeller = labeller(included = c(`cycling` = 'Naturally cycling', `horm_contra` = 'Hormonal contraceptive user'))) +
geom_segment(aes(x = if_else(included=="cycling",-14,NA_real_), xend = if_else(included=="cycling",-14,NA_real_)), color = 'darkred', linetype = 'dashed', y = 0.7, yend = 17.7)+
geom_text(data = data.frame(included = 'cycling', variable.f = 1, RCD_inferred = -14), label = 'est. day of ovulation', color = 'darkred', y = 0.5)
}
ggsave(ts_plot, file = "item_timeseries2.pdf", width = 10, height = 10)
ts_plot</code></pre>
<p><img src="3_stan_brms_long2_files/figure-html/unnamed-chunk-4-1.png" width="1152" /></p>
</div>
</div>
</div>
<script>
// add bootstrap table styles to pandoc tables
function bootstrapStylePandocTables() {
$('tr.header').parent('thead').parent('table').addClass('table table-condensed');
}
$(document).ready(function () {
bootstrapStylePandocTables();
});
</script>
<!-- dynamically load mathjax for compatibility with self-contained -->
<script>
(function () {
var script = document.createElement("script");
script.type = "text/javascript";
script.src = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML";
document.getElementsByTagName("head")[0].appendChild(script);
})();
</script>
</body>
</html>