minor edits to Shiny apps

scripts/DevWorkshop/ROC-power/shinyapp/basic-app/app.py

@@ -3,7 +3,7 @@
 from numpy import random
 from three_panel import *
 
-app_ui = ui.page_fixed(ui.panel_title("Sample Size for Comparing Models' Area Under the ROC Curve:", "Sample Size for Comparing AUROCs"),  
+app_ui = ui.page_fluid(ui.panel_title("Sample Size for Comparing Models' Area Under the ROC Curve:", "Sample Size for Comparing AUROCs"),  
     ui.h4("Specifying parameters of two joint distributions"), 
     ui.row(
         ui.column(
@@ -33,7 +33,7 @@
             ui.input_numeric("ss", label="- Sample Size", value=260, min=100, max=100000),
             ui.input_slider("prev", label="- Prevalence", value=.1, step=.01, min=1e-2, max=1-1e-2),
             ui.input_slider("alpha_t", label="- Alpha threshold", value=.05, step=.01, min=1e-2, max=1-1e-2),
-            ui.input_select("n_sim", label=ui.markdown("**Choose no. of iterations to run the simulations**"), choices={0: "Zero (for parameter selection)", 100: "100 simulations (fastest, least accurate)", 500: "500 simulations (intermediate)", 2000: "2000 simulations (slowest, most accurate)"}),
+            ui.input_select("n_sim", label=ui.markdown("**Run the simulations**"), choices={0: "No iteration (for parameter selection)", 100: "100 iterations (fastest, least accurate)", 500: "500 iterations (intermediate)", 2000: "2000 iterations (slowest, most accurate)"}),
         )
     ),
     ui.row(

scripts/DevWorkshop/ROC-power/shinyapp/collins/rsconnect-python/collins.json

@@ -5,7 +5,7 @@
         "app_url": "https://francois-grolleau.shinyapps.io/prec_auroc1/",
         "app_id": 12432652,
         "app_guid": null,
-        "title": "prec_auroc",
+        "title": "prec_auroc1",
         "app_mode": "python-shiny",
         "app_store_version": 1
     }

scripts/DevWorkshop/ROC-power/shinyapp/index.html

@@ -52,7 +52,7 @@
             margin-top: 10px; /* Add space between list items */
         }
         .dash-list li::before {
-            content: "-";
+            content: "\2192";
             margin-right: 8px;
         }
         .zoom-link {
@@ -79,19 +79,19 @@
 <div class="content">
     <div id="intro_page">
         <h2>powerROC v0.1</h2>
-        <p>For the evaluation of clinical prediction models, the <a href="https://www.bmj.com/content/385/bmj-2023-078378" target="_blank">TRIPOD+AI statement</a> requires that researchers report how the sample size was arrived at and justify that this sample size was sufficient to answer the research question.</p>
+        <p>For the evaluation of clinical prediction models, the <a href="https://www.bmj.com/content/385/bmj-2023-078378" target="_blank">TRIPOD+AI statement</a> mandates reporting the process of determining the sample size and justifying its sufficiency in addressing the research question.</p>
         <p>powerROC is a web application that helps researchers determine the sample size required to estimate the area under the receiver operating characteristic curve (AUROC) with a desired level of precision or to compare the AUROCs of two models with a desired level of power.</p>
 
         <ul class="dash-list">
             <li><b>For evaluating a single prediction model</b></li>
-            <p style="text-indent: 40px;">click <a href="#" onclick="showContent('page1')" class="zoom-link">Sample size to precisely estimate the AUROC</a> </p> <p style="text-indent: 40px;">to find the sample size required for accurate AUROC estimation.</p>
+            <p style="text-indent: 40px;">click <a href="#" onclick="showContent('page1')" class="zoom-link">Sample size to precisely estimate the AUROC.</a></p>
             <li><b>For comparing two prediction models</b>
-                <p style="text-indent: 20px;">With acess to a pilot test set (or a validation set from which you will vary the prevalence),</p><p style="text-indent: 40px;">click <a href="#" onclick="showContent('page2')" class="zoom-link">Sample size for comparing AUROCs: using a pilot test set</a> </p> <p style="text-indent: 40px;">to determine sample size based on pilot data.</p>
-                <p style="text-indent: 20px;">Without acess to a pilot test set or a validation set,</p><p style="text-indent: 40px;">click <a href="#" onclick="showContent('page3')" class="zoom-link">Sample size for comparing AUROCs: specifying joint distributions</a> </p> <p style="text-indent: 40px;">to calculate sample size without needing preliminary data.</p>
+                <p style="text-indent: 20px;">- With acess to a pilot test set (or a validation set from which you may want to vary the prevalence),</p><p style="text-indent: 40px;">click <a href="#" onclick="showContent('page2')" class="zoom-link">Sample size for comparing AUROCs: using a pilot test set</a> </p> <p style="text-indent: 40px;">to determine sample size based on pilot data.</p>
+                <p style="text-indent: 20px;">- Without acess to a pilot test set or a validation set,</p><p style="text-indent: 40px;">click <a href="#" onclick="showContent('page3')" class="zoom-link">Sample size for comparing AUROCs: specifying joint distributions</a> </p> <p style="text-indent: 40px;">to calculate sample size without needing preliminary data.</p>
             </li>
         </ul>
         <br>
-        For any inquiries or further assistance, please contact François Grolleau at grolleau@stanford.edu.<br>
+        For any inquiries or further assistance, please contact François Grolleau at grolleau [ a t ] stanford.edu.<br>
         © 2024 PowerROC. All rights reserved.
     </div>
     <div id="page1" class="hidden">

scripts/DevWorkshop/ROC-power/shinyapp/pilot/app.py

@@ -5,15 +5,15 @@
 
 app_ui = ui.page_fluid(ui.panel_title("Sample Size for Comparing Models' Area Under the ROC Curve:", "Sample Size for Comparing AUROCs"),
     ui.h4("Using a pilot test set"), ui.br(),
-    ui.input_file("file1", "Upload a pilot test set as a CSV file", accept=[".csv"], multiple=False),
+    ui.input_file("file1", "Upload a pilot test set, with at least three events and three nonevents, as a CSV file", accept=[".csv"], multiple=False),
     ui.output_text("text"),
     ui.output_table("summary_csv"),
     ui.input_switch("change_prev", "Change prevalence", False),
     ui.output_ui("ui_prev"),
     ui.row(
     ui.input_numeric("ss", label="Sample Size", value=1060, min=100, max=100000),
     ui.input_slider("alpha_t", label="Alpha threshold", value=.05, step=.01, min=1e-2, max=1-1e-2),
-    ui.input_select("n_sim", label=ui.markdown("**Choose no. of iterations to run the simulations**"), choices={100: "100 simulations (fastest, least accurate)", 500: "500 simulations (intermediate)", 2000: "2000 simulations (slowest, most accurate)"}),
+    ui.input_select("n_sim", label=ui.markdown("**Run the simulations**"), choices={100: "100 iteration (fastest, least accurate)", 500: "500 iterations (intermediate)", 2000: "2000 iterations (slowest, most accurate)"}),
 ),
     ui.row(ui.output_plot("int_plot", width='1000px', height='750px'),),
 )

scripts/DevWorkshop/ROC-power/shinyapp/pilot/three_panel_pilot.py

@@ -87,7 +87,7 @@ def three_panel_pilot(data,
     if change_prev:
         plt.title(f'Assuming the distribution from the provided pilot test set with a prevalence of {100*prev:.0f}%,\n the true AUROCs are {auc_A:.2f} for Model A and {auc_B:.2f} for Model B,\nbased on {n_sim} simulations, the estimated power to detect a difference in AUROC is:', fontsize=14, y=1.15)
     else:
-         plt.title(f'Assuming the distribution from the provided pilot test set,\n the true AUROCs are {auc_A:.2f} for Model A and {auc_B:.2f} for Model B,\nbased on {n_sim} simulations, the estimated power to detect a difference in AUROC is:', fontsize=14, y=1.15)
+         plt.title(f'Assuming the distribution from the provided pilot test set,\n the true AUROCs are {auc_A:.2f} for Model A and {auc_B:.2f} for Model B,\nand based on {n_sim} simulations, the estimated power to detect a difference in AUROC is:', fontsize=14, y=1.15)
 
     # add power as text
     plt.text(sample_sizes[0], 1.02, f'Power is {powers[0]*100:.1f}%\nAt n={sample_sizes[0]}', ha='center', va='bottom', transform=plt.gca().get_xaxis_transform())