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<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">outcome =<span class="st"> </span><span class="kw">names</span>(model@frame)[<span class="dv">1</span>]
outcome_label =<span class="st"> </span><span class="kw">recode</span>(<span class="kw">str_replace_all</span>(<span class="kw">str_replace_all</span>(<span class="kw">str_replace_all</span>(outcome, <span class="st">"_"</span>, <span class="st">" "</span>), <span class="st">" pair"</span>, <span class="st">"-pair"</span>), <span class="st">" 1"</span>, <span class="st">""</span>),
<span class="st">"desirability 1"</span> =<span class="st"> "self-perceived desirability"</span>,
<span class="st">"NARQ admiration"</span> =<span class="st"> "narcissistic admiration"</span>,
<span class="st">"NARQ rivalry"</span> =<span class="st"> "narcissistic rivalry"</span>,
<span class="st">"extra-pair"</span> =<span class="st"> "extra-pair desire & behaviour"</span>,
<span class="st">"had sexual intercourse"</span> =<span class="st"> "sexual intercourse"</span>)
<span class="kw">library</span>(ggplot2)
<span class="co"># form a subset and run the model without the hormonal contraception and the fertility predictors</span>
tmp =<span class="st"> </span>diary %>%
<span class="st"> </span><span class="kw">filter</span>(!<span class="kw">is.na</span>(fertile), !<span class="kw">is.na</span>(included),
RCD ><span class="st"> </span>-<span class="dv">1</span> *<span class="st"> </span>minimum_cycle_length_diary, RCD ><span class="st"> </span>-<span class="dv">40</span>)
new_form =<span class="st"> </span><span class="kw">update.formula</span>(<span class="kw">formula</span>(model), <span class="dt">new =</span> . ~<span class="st"> </span>. -<span class="st"> </span>fertile *<span class="st"> </span>included)
tmp$residuals =<span class="st"> </span><span class="kw">residuals</span>(<span class="kw">update</span>(model, new_form, <span class="dt">data =</span> tmp , <span class="dt">na.action =</span> na.exclude))
tmp =<span class="st"> </span>tmp %>%<span class="st"> </span>
<span class="st"> </span><span class="kw">filter</span>(!<span class="kw">is.na</span>(RCD), !<span class="kw">is.na</span>(residuals))
rcd_min =<span class="st"> </span><span class="kw">min</span>(tmp$RCD)
tmp$real =<span class="st"> </span><span class="ot">FALSE</span>
tmp_before =<span class="st"> </span>tmp
tmp_before$RCD =<span class="st"> </span>tmp_before$RCD +<span class="st"> </span><span class="kw">min</span>(tmp$RCD) -<span class="st"> </span><span class="dv">1</span>
tmp_after =<span class="st"> </span>tmp
tmp_after$RCD =<span class="st"> </span>tmp_after$RCD -<span class="st"> </span><span class="kw">min</span>(tmp$RCD) +<span class="st"> </span><span class="dv">1</span>
tmp$real =<span class="st"> </span><span class="ot">TRUE</span>
tmp =<span class="st"> </span><span class="kw">bind_rows</span>(tmp_before %>%<span class="st"> </span><span class="kw">filter</span>(RCD ><span class="st"> </span>rcd_min -<span class="st"> </span><span class="dv">11</span>), tmp, tmp_after %>%<span class="st"> </span><span class="kw">filter</span>(RCD <<span class="st"> </span><span class="dv">11</span>))</code></pre></div>
<div id="gam-smooth-on-residuals" class="section level6">
<h6>GAM smooth on residuals</h6>
<p>Here, we partialled out menstruation and individual random effects, then superimposed estimated conception risk scaled to the range of the estimated means. To address the periodicity of the cycle, we prepended and appended ten days of the timeseries to the end and the beginning of the timeseries. We then estimated the GAM and cut off the appended subsets before plotting.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">tryCatch</span>({
trend_plot =<span class="st"> </span><span class="kw">ggplot</span>(tmp,<span class="kw">aes</span>(<span class="dt">x =</span> RCD, <span class="dt">y =</span> residuals, <span class="dt">colour =</span> included)) +
<span class="st"> </span><span class="kw">stat_smooth</span>(<span class="dt">geom =</span> <span class="st">'smooth'</span>,<span class="dt">size =</span> <span class="fl">0.8</span>, <span class="dt">fill =</span> <span class="st">"#9ECAE1"</span>, <span class="dt">method =</span> <span class="st">'gam'</span>, <span class="dt">formula =</span> y ~<span class="st"> </span><span class="kw">s</span>(x))
}, <span class="dt">error =</span> function(e){<span class="kw">cat_message</span>(e, <span class="st">"danger"</span>)})
<span class="kw">tryCatch</span>({
trend_data =<span class="st"> </span><span class="kw">ggplot_build</span>(trend_plot)$data[[<span class="dv">1</span>]]
}, <span class="dt">error =</span> function(e){<span class="kw">cat_message</span>(e, <span class="st">"danger"</span>)})
trend_data$RCD =<span class="st"> </span><span class="kw">round</span>(trend_data$x)
trend_data =<span class="st"> </span><span class="kw">left_join</span>(trend_data, tmp %>%<span class="st"> </span><span class="kw">select</span>(real, RCD,fertile) %>%<span class="st"> </span><span class="kw">unique</span>(), <span class="dt">by =</span> <span class="st">"RCD"</span>)
trend_data %>%
<span class="st"> </span><span class="kw">filter</span>(real ==<span class="st"> </span><span class="ot">TRUE</span>) %>%
<span class="st"> </span><span class="kw">mutate</span>(<span class="dt">superimposed =</span> ( ( (fertile -<span class="st"> </span><span class="fl">0.01</span>)/<span class="fl">0.58</span>) *<span class="st"> </span>(<span class="kw">max</span>(y)-<span class="kw">min</span>(y) ) ) +<span class="st"> </span><span class="kw">min</span>(y) ) ->
<span class="st"> </span>trend_data
<span class="kw">ggplot</span>(trend_data) +
<span class="st"> </span><span class="kw">geom_ribbon</span>(<span class="kw">aes</span>(<span class="dt">x =</span> x, <span class="dt">ymin =</span> ymin, <span class="dt">ymax =</span> ymax, <span class="dt">fill =</span> <span class="kw">factor</span>(group)), <span class="dt">alpha =</span> <span class="fl">0.2</span>) +
<span class="st"> </span><span class="kw">geom_line</span>(<span class="kw">aes</span>(<span class="dt">x =</span> x, <span class="dt">y =</span> y, <span class="dt">colour =</span> <span class="kw">factor</span>(group)), <span class="dt">size =</span> <span class="fl">0.8</span>, <span class="dt">stat =</span> <span class="st">"identity"</span>) +
<span class="st"> </span><span class="kw">scale_x_continuous</span>(caption_x) +
<span class="st"> </span><span class="kw">geom_line</span>(<span class="kw">aes</span>(<span class="dt">x =</span> x, <span class="dt">y =</span> superimposed), <span class="dt">color =</span> <span class="st">"#a83fbf"</span>, <span class="dt">size =</span> <span class="dv">1</span>, <span class="dt">linetype =</span> <span class="st">'dashed'</span>) +
<span class="st"> </span><span class="kw">annotate</span>(<span class="st">"text"</span>,<span class="dt">x =</span> <span class="kw">mean</span>(trend_data$x), <span class="dt">y =</span> <span class="kw">max</span>(trend_data$superimposed,<span class="dt">na.rm=</span>T) +<span class="st"> </span><span class="fl">0.1</span>, <span class="dt">label =</span> <span class="st">'superimposed fertility peak'</span>, <span class="dt">color =</span> <span class="st">"#a83fbf"</span>) +
<span class="st"> </span><span class="kw">scale_y_continuous</span>(outcome_label) +
<span class="st"> </span><span class="kw">ggtitle</span>(<span class="st">"GAM smooth, residuals"</span>) +
<span class="st"> </span><span class="kw">scale_color_manual</span>(<span class="st">"Contraception status"</span>,<span class="dt">values =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"black"</span>,<span class="st">"1"</span>=<span class="st"> "red"</span>), <span class="dt">labels =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"hormonally</span><span class="ch">\n</span><span class="st">contracepting"</span>,<span class="st">"1"</span>=<span class="st">"cycling"</span>), <span class="dt">guide =</span> F) +
<span class="st"> </span><span class="kw">scale_fill_manual</span>(<span class="st">"Contraception status"</span>,<span class="dt">values =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"black"</span>,<span class="st">"1"</span>=<span class="st"> "red"</span>), <span class="dt">labels =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"hormonally</span><span class="ch">\n</span><span class="st">contracepting"</span>,<span class="st">"1"</span>=<span class="st">"cycling"</span>), <span class="dt">guide =</span> F)</code></pre></div>
</div>
<div id="gam-smooth-on-raw-data" class="section level6">
<h6>GAM smooth on raw data</h6>
<p>As before, but without partialling anything out.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">tryCatch</span>({
trend_plot =<span class="st"> </span><span class="kw">ggplot</span>(tmp,<span class="kw">aes_string</span>(<span class="dt">x =</span> <span class="st">"RCD"</span>, <span class="dt">y =</span> outcome, <span class="dt">colour =</span> <span class="st">"included"</span>)) +
<span class="st"> </span><span class="kw">stat_smooth</span>(<span class="dt">geom =</span> <span class="st">'smooth'</span>,<span class="dt">size =</span> <span class="fl">0.8</span>, <span class="dt">fill =</span> <span class="st">"#9ECAE1"</span>, <span class="dt">method =</span> <span class="st">'gam'</span>, <span class="dt">formula =</span> y ~<span class="st"> </span><span class="kw">s</span>(x))
}, <span class="dt">error =</span> function(e){<span class="kw">cat_message</span>(e, <span class="st">"danger"</span>)})
<span class="kw">tryCatch</span>({
trend_data =<span class="st"> </span><span class="kw">ggplot_build</span>(trend_plot)$data[[<span class="dv">1</span>]]
}, <span class="dt">error =</span> function(e){<span class="kw">cat_message</span>(e, <span class="st">"danger"</span>)})
trend_data$RCD =<span class="st"> </span><span class="kw">round</span>(trend_data$x)
trend_data =<span class="st"> </span><span class="kw">left_join</span>(trend_data, tmp %>%<span class="st"> </span><span class="kw">select</span>(real, RCD,fertile) %>%<span class="st"> </span><span class="kw">unique</span>(), <span class="dt">by =</span> <span class="st">"RCD"</span>)
trend_data %>%
<span class="st"> </span><span class="kw">filter</span>(real ==<span class="st"> </span><span class="ot">TRUE</span>) %>%
<span class="st"> </span><span class="kw">mutate</span>(<span class="dt">superimposed =</span> ( ( (fertile -<span class="st"> </span><span class="fl">0.01</span>)/<span class="fl">0.58</span>) *<span class="st"> </span>(<span class="kw">max</span>(y)-<span class="kw">min</span>(y) ) ) +<span class="st"> </span><span class="kw">min</span>(y) ) ->
<span class="st"> </span>trend_data
plot1b =<span class="st"> </span><span class="kw">ggplot</span>(trend_data) +
<span class="st"> </span><span class="kw">geom_ribbon</span>(<span class="kw">aes</span>(<span class="dt">x =</span> x, <span class="dt">ymin =</span> ymin, <span class="dt">ymax =</span> ymax, <span class="dt">fill =</span> <span class="kw">factor</span>(group)), <span class="dt">alpha =</span> <span class="fl">0.2</span>) +
<span class="st"> </span><span class="kw">geom_line</span>(<span class="kw">aes</span>(<span class="dt">x =</span> x, <span class="dt">y =</span> y, <span class="dt">colour =</span> <span class="kw">factor</span>(group)), <span class="dt">size =</span> <span class="fl">0.8</span>, <span class="dt">stat =</span> <span class="st">"identity"</span>) +
<span class="st"> </span><span class="kw">scale_x_continuous</span>(caption_x) +
<span class="st"> </span><span class="kw">geom_line</span>(<span class="kw">aes</span>(<span class="dt">x =</span> x, <span class="dt">y =</span> superimposed), <span class="dt">color =</span> <span class="st">"#a83fbf"</span>, <span class="dt">size =</span> <span class="dv">1</span>, <span class="dt">linetype =</span> <span class="st">'dashed'</span>) +
<span class="st"> </span><span class="kw">annotate</span>(<span class="st">"text"</span>,<span class="dt">x =</span> <span class="kw">mean</span>(trend_data$x), <span class="dt">y =</span> <span class="kw">max</span>(trend_data$superimposed,<span class="dt">na.rm=</span>T) +<span class="st"> </span><span class="fl">0.1</span>, <span class="dt">label =</span> <span class="st">'superimposed fertility peak'</span>, <span class="dt">color =</span> <span class="st">"#a83fbf"</span>) +
<span class="st"> </span><span class="kw">scale_y_continuous</span>(outcome_label) +
<span class="st"> </span><span class="kw">ggtitle</span>(<span class="st">"GAM smooth, raw data"</span>) +
<span class="st"> </span><span class="kw">scale_color_manual</span>(<span class="st">"Contraception status"</span>,<span class="dt">values =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"black"</span>,<span class="st">"1"</span>=<span class="st"> "red"</span>), <span class="dt">labels =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"hormonally</span><span class="ch">\n</span><span class="st">contracepting"</span>,<span class="st">"1"</span>=<span class="st">"cycling"</span>), <span class="dt">guide =</span> F) +
<span class="st"> </span><span class="kw">scale_fill_manual</span>(<span class="st">"Contraception status"</span>,<span class="dt">values =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"black"</span>,<span class="st">"1"</span>=<span class="st"> "red"</span>), <span class="dt">labels =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"hormonally</span><span class="ch">\n</span><span class="st">contracepting"</span>,<span class="st">"1"</span>=<span class="st">"cycling"</span>), <span class="dt">guide =</span> F)
<span class="kw">suppressWarnings</span>(<span class="kw">print</span>(plot1b))</code></pre></div>
</div>
<div id="means-and-standard-errors-over-raw-data" class="section level6">
<h6>Means and standard errors over raw data</h6>
<p>Nothing partialled out, just straight means with bootstrapped confidence intervals.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">tryCatch</span>({
trend_plot =<span class="st"> </span><span class="kw">ggplot</span>(tmp,<span class="kw">aes_string</span>(<span class="dt">x =</span> <span class="st">"RCD"</span>, <span class="dt">y =</span> outcome, <span class="dt">colour =</span> <span class="st">"included"</span>)) +
<span class="st"> </span><span class="kw">geom_pointrange</span>(<span class="dt">size =</span> <span class="fl">0.8</span>, <span class="dt">stat =</span> <span class="st">'summary'</span>, <span class="dt">fun.data =</span> <span class="st">"mean_cl_boot"</span>)
}, <span class="dt">error =</span> function(e){<span class="kw">cat_message</span>(e, <span class="st">"danger"</span>)})
<span class="kw">tryCatch</span>({
trend_data =<span class="st"> </span><span class="kw">ggplot_build</span>(trend_plot)$data[[<span class="dv">1</span>]]
}, <span class="dt">error =</span> function(e){<span class="kw">cat_message</span>(e, <span class="st">"danger"</span>)})
trend_data$RCD =<span class="st"> </span><span class="kw">round</span>(trend_data$x)
trend_data =<span class="st"> </span><span class="kw">left_join</span>(trend_data, tmp %>%<span class="st"> </span><span class="kw">select</span>(real, RCD,fertile) %>%<span class="st"> </span><span class="kw">unique</span>(), <span class="dt">by =</span> <span class="st">"RCD"</span>)
trend_data %>%
<span class="st"> </span><span class="kw">filter</span>(real ==<span class="st"> </span><span class="ot">TRUE</span>) %>%
<span class="st"> </span><span class="kw">mutate</span>(<span class="dt">superimposed =</span> ( ( (fertile -<span class="st"> </span><span class="fl">0.01</span>)/<span class="fl">0.58</span>) *<span class="st"> </span>(<span class="kw">max</span>(y)-<span class="kw">min</span>(y) ) ) +<span class="st"> </span><span class="kw">min</span>(y) ) ->
<span class="st"> </span>trend_data
plot3 =<span class="st"> </span><span class="kw">ggplot</span>(trend_data) +
<span class="st"> </span><span class="kw">geom_pointrange</span>(<span class="kw">aes</span>(<span class="dt">x =</span> x, <span class="dt">y =</span> y, <span class="dt">ymin =</span> ymin,<span class="dt">ymax =</span> ymax, <span class="dt">colour =</span> <span class="kw">factor</span>(group)), <span class="dt">size =</span> <span class="fl">0.8</span>, <span class="dt">stat =</span> <span class="st">"identity"</span>, <span class="dt">alpha =</span> <span class="fl">0.6</span>, <span class="dt">position =</span> <span class="kw">position_dodge</span>(<span class="dt">width =</span> .<span class="dv">5</span>)) +
<span class="st"> </span><span class="kw">scale_x_continuous</span>(<span class="st">"Days until next menstruation"</span>) +
<span class="st"> </span><span class="kw">geom_line</span>(<span class="kw">aes</span>(<span class="dt">x=</span> x, <span class="dt">y =</span> superimposed), <span class="dt">color =</span> <span class="st">"#a83fbf"</span>, <span class="dt">size =</span> <span class="dv">1</span>, <span class="dt">linetype =</span> <span class="st">'dashed'</span>) +
<span class="st"> </span><span class="kw">annotate</span>(<span class="st">"text"</span>,<span class="dt">x =</span> <span class="kw">mean</span>(trend_data$x), <span class="dt">y =</span> <span class="kw">max</span>(trend_data$superimposed,<span class="dt">na.rm=</span>T) +<span class="st"> </span><span class="fl">0.1</span>, <span class="dt">label =</span> <span class="st">'superimposed fertility peak'</span>, <span class="dt">color =</span> <span class="st">"#a83fbf"</span>) +
<span class="st"> </span><span class="kw">scale_y_continuous</span>(outcome_label) +
<span class="st"> </span><span class="kw">ggtitle</span>(<span class="st">"Means with standard errors, raw data"</span>) +
<span class="st"> </span><span class="kw">scale_color_manual</span>(<span class="st">"Contraception status"</span>,<span class="dt">values =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"black"</span>,<span class="st">"1"</span>=<span class="st"> "red"</span>), <span class="dt">labels =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"hormonally</span><span class="ch">\n</span><span class="st">contracepting"</span>,<span class="st">"1"</span>=<span class="st">"cycling"</span>), <span class="dt">guide =</span> F) +
<span class="st"> </span><span class="kw">scale_fill_manual</span>(<span class="st">"Contraception status"</span>,<span class="dt">values =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"black"</span>,<span class="st">"1"</span>=<span class="st"> "red"</span>), <span class="dt">labels =</span> <span class="kw">c</span>(<span class="st">"2"</span>=<span class="st">"hormonally</span><span class="ch">\n</span><span class="st">contracepting"</span>,<span class="st">"1"</span>=<span class="st">"cycling"</span>), <span class="dt">guide =</span> F)
<span class="kw">suppressWarnings</span>(<span class="kw">print</span>(plot3))</code></pre></div>
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