Pooled Diagnostic Metrics Computation

@ShaikhAneesa

Hi there, I’ve reviewed your requirement and understand you need pooled sensitivity and specificity from an Excel dataset, along with 95% confidence intervals, a ROC curve, and fully reproducible code for auditability. I can handle this using either R or Python depending on what you prefer, with a strong emphasis on statistical correctness and transparency. My approach will start by importing your Excel data and validating the structure (true positives, false positives, true negatives, false negatives or equivalent classification columns). I will then compute sensitivity and specificity at the observation level and apply an appropriate pooling method (fixed-effect or random-effects depending on heterogeneity). Confidence intervals will be calculated using standard binomial or meta-analytic methods as appropriate. For diagnostic performance, I will generate a ROC curve using threshold-based analysis and compute AUC to quantify overall discrimination ability. The output will include both the plotted ROC curve (exported as a high-resolution image) and the underlying coordinate data so you can fully trace or reuse the analysis. To ensure the correct methodology, could you confirm whether your dataset includes multiple studies (requiring meta-analysis) or a single diagnostic dataset with repeated observations? I’m ready to start immediately. Warm Regards, Aneesa.

@WelcomeClient

Hi There, Ready right now I'm ready to pull the data directly from the Excel file, run whatever pooling or meta-analytic technique is most appropriate, and return. I will show you sample for your satisfaction and project accuracy then we will go to start, so please contact me and share more details thanks. Check My Profile: https://www.freelancer.pk/u/WelcomeClient I would like to work on this project and can complete with 100% accuracy within the time frame. https://www.freelancer.pk/projects/excel/business-profit-loss-reporting-excel/reviews https://www.freelancer.pk/projects/data-entry/copy-listings-from-website-another/reviews Thanks, Umer

@HiraMahmood4072

Hello, With over 7 years of experience in Excel, R Programming Language, Data Visualization, Statistical Analysis, Statistical Modeling, and Statistics, I have the expertise required for your project. I have carefully read the requirements for the computation of pooled diagnostic metrics from an Excel spreadsheet. I will extract the data directly from the Excel file and utilize the most appropriate pooling or meta-analytic technique to calculate the pooled sensitivity and specificity. The deliverables will include a results table displaying pooled sensitivity, specificity, and their 95% CIs, an ROC curve with underlying coordinates, and the code or reproducible steps used for transparency and future reference. I am proficient in R, Python (scikit-learn), and Stata, ensuring that the final outputs align with your expectations and are well-documented. I would appreciate the opportunity to discuss the project further in chat to address any additional details or questions you may have. You can visit my Profile: https://www.freelancer.com/u/HiraMahmood4072 Thank you.

@OlektraGroup

Hi there. You need to derive pooled sensitivity, specificity, and 95% CIs from your observation-level Excel data, visualized via an audit-ready ROC curve. I recently handled a similar diagnostic task for an MRI reconstruction project where I processed raw observation data to validate model performance metrics. I will use the R ‘mada’ package to perform a bivariate meta-analysis, which is the gold standard for pooling diagnostic accuracy while accounting for the trade-off between sensitivity and specificity. I’ll provide the full R script, a high-resolution ROC plot, and a clean results table for your records. Given your spreadsheet structure, are the "True Positive" and "False Positive" statuses already flagged, or do I need to define the binary classification thresholds based on your reference standard column?

@nrajuu07

Having spent a significant part of my career working on medical data, I've developed extensive skills in statistical analysis and can more than cater to your needs for this project. My expertise with machine learning and deep learning models like YOLOv8, UNet, ViT, and others align perfectly with your need for indicative ROC curves and pooled diagnostic metrics computation. I also have a comprehensive understanding of medical image analysis and computer vision techniques that will ensure efficient handling of your medical dataset. In a world where data needs are constantly evolving, having an adaptable approach is crucial. I am comfortable with using a range of statistical packages including R, Python (scikit-learn), and Stata – ensuring there's no limitation on what we can achieve together for your project. In summary, my interdisciplinary experience, deep knowledge of relevant methods, commitment to transparency and delivery of production-ready AI systems make me the best fit for your project. Let's connect to further discuss how I can best assist you.

@Feriver

Hello, I understand you need a statistically rigorous computation of pooled diagnostic performance metrics from your Excel dataset, including sensitivity, specificity, confidence intervals, and ROC analysis. I have strong experience in biostatistics, diagnostic accuracy studies, and reproducible analysis using Python (scikit-learn, statsmodels) and R. I will directly import your Excel file, validate the structure, and apply an appropriate pooling or meta-analytic approach for sensitivity and specificity depending on study design. I will compute 95% confidence intervals using standard statistical methods (e.g., binomial or hierarchical models where applicable). You will receive a clean results table with pooled sensitivity and specificity, a fully reproducible script (Python or R depending on preference), and a ROC curve exported as both an image and raw coordinate data. The workflow will be fully documented so you can rerun or extend the analysis at any time. Thanks, Asif.

@muneeb6767

I can compute pooled sensitivity/specificity using proper meta-analysis (bivariate/HSROC), generate 95% CIs + ROC curve, and deliver clean results with reproducible R/Python code. You’ll get a clear results table, ROC image + coordinates, and documented steps so you can audit or rerun anytime.

@Muhammadzeesha59

As an experienced data analyst with over 6 years of experience, I have a deep proficiency in Python, the very skill you're looking for in this project. My data analysis and visualization skills have been fine-tuned specifically for tasks like yours, where accurate results and clear visualizations are pivotal. Whether it's using R, Python (scikit-learn), Stata or any other statistical software you prefer, rest assured I will generate precisely what you're looking for: pooled sensitivity, specificity, their 95% CIs as well as the ROC curve. To facilitate any future updates or audits, I consistently create detailed and reproducible codes along with a thorough documentation process. My commitment to quality and meticulousness has earned me accolades from clients globally since 2018. You can rely on me to provide the highest quality solutions within a reasonable budget and timeline. Thus, by choosing me for your project, you're not only getting a seasoned professional but also someone who takes pride in delivering work that meets the highest standards. Your data deserves meticulous attention and that's exactly what I offer as part of my bespoke service package. Let's make your Excel spreadsheet work intelligently for you!

@EhtishamHaider1

As an Electrical Engineer turned Data Scientist, I bring to the table a rich combination of skills and experiences that match your project requirements perfectly. My repertoire boasts proficiency in Python for data manipulation and analysis which will be tremendously helpful in extracting the necessary information from your Excel spreadsheet. Moreover, my mastery over data visualization methods, including those with Python, is essential when generating ROC curves. Robustness and reproducibility are two key features of my work. I understand your need to have not just the final results but also a transparent understanding of how they were derived. That is why, whether we use R or Python (scikit-learn), you can be rest assured that your requested code or reproducible steps will be meticulous and well-commented.

@khaliduom103

‎Hi I am experienced data analyst of all types of raw data.I will provide my previous project output in the chat box.I have expertise in python for all types of data analysis. ‎

@Bhartifreelancer

Hell, I work proficiently with data analysis and am adept in handling large datasets like your Excel spreadsheet. Using either R, Python (scikit-learn), Stata or another software of your preference, I can efficiently pull the data, analyze it using the most suitable pooling and meta-analytic techniques and deliver precise outputs such as pooled sensitivity, specificity with their 95% confidence intervals and a comprehensive ROC curve with both image file and underlying coordinates. I appreciate that you want the approach to be clearly documented and reproducible so that it can be audited or modified in the future. I assure you that you will receive well-commented code and step-by-step instructions to ensure transparency in the analysis process. Best regards Bharti

@Freelancersedo

Hello, I can analyse your Excel dataset and compute pooled sensitivity and specificity using the most appropriate diagnostic meta-analytic approach based on the structure of your data. I will deliver a clear results table with pooled estimates and 95% confidence intervals, generate an ROC curve with both image output and underlying coordinates, and provide fully reproducible code or step-by-step methods in R, Python, Stata, or your preferred software. All data will be pulled directly from the Excel file, with methods clearly documented so you can verify, update, or reuse the analysis confidently.

@jonathangleon

Hi there, I’ve reviewed your requirements, and this aligns well with my experience in Python/R data analysis and statistical reporting. I can pull the data directly from your Excel file, calculate pooled sensitivity and specificity with 95% confidence intervals using an appropriate meta-analytic approach, and generate the ROC curve with both image output and underlying coordinates. Best regards Jonthan

@debianguy

Hi, this is not a basic aggregation task—getting pooled sensitivity/specificity right requires a proper statistical approach, and that’s exactly what I deliver. I’ll process your Excel dataset end-to-end in Python (pandas, numpy, statsmodels), validating structure and preparing it for diagnostic meta-analysis. Instead of naïve averaging, I’ll implement a bivariate random-effects model (Reitsma-style approximation) to obtain robust pooled sensitivity and specificity with correct 95% confidence intervals. I’ll also generate a summary ROC (SROC) curve, including a publication-ready image and the underlying TPR/FPR coordinates using scikit-learn. You’ll receive: Results table (pooled estimates + 95% CIs) SROC curve (image + raw data) Reproducible, well-documented Python code Data should be provided as TP/FP/FN/TN per observation, or sensitivity/specificity with enough detail to reconstruct them. I focus on correctness and reproducibility—no shortcuts. Happy to review your dataset before starting.

@CauaAlves

Dear Client, I am ready to compute the pooled diagnostic metrics (sensitivity and specificity with 95% confidence intervals) and generate the ROC curve from your Excel dataset. Approach: Load data directly from the provided Excel file Apply appropriate pooling/meta-analytic method (bivariate model or fixed/random effects as best suited for your data) Calculate pooled sensitivity, specificity and their 95% CIs Generate ROC curve (image + full coordinate table) Deliverables: Clean results table with pooled sensitivity, specificity and 95% CIs High-quality ROC curve image + underlying data points (coordinates) Complete, well-commented Python code (or R if preferred) with clear steps for reproducibility and future updates The solution will be accurate, documented and easy to audit or modify. I specialize in statistical analysis and diagnostic meta-analysis in Python and can start immediately. Looking forward to delivering this for you.

@MIndlabsAi6

Hello, I am Vishal Maharaj, with 20 years of experience in Python, R Programming Language, and Data Visualization. I have carefully reviewed your project requirements for calculating pooled sensitivity and specificity from an Excel dataset. To accomplish this task, I will extract the data from the Excel file, apply appropriate pooling techniques, and generate the required results. I will provide a results table displaying pooled sensitivity, specificity, and their 95% CIs, along with an ROC curve for visual representation. The code or steps used will be documented for future reference. I am proficient in statistical packages like R, Python (scikit-learn), and Stata. Please initiate a chat to discuss the project further. Cheers, Vishal Maharaj

@RavenDetector

Hi there, I understand that you need to compute pooled diagnostic metrics from your Excel dataset, including sensitivity, specificity, and their confidence intervals, along with generating a ROC curve for visual analysis. I have extensive experience in statistical analysis and data visualization using both R and Python, which gives me the flexibility to choose the most suitable package for your needs. To meet your requirements, I will first pull the data directly from your Excel file. I will then apply the appropriate meta-analytic techniques to calculate the pooled sensitivity and specificity, ensuring that the results are well-documented. The concise results table will include the pooled metrics and 95% confidence intervals. Additionally, I will generate the ROC curve and provide you with the underlying coordinates along with clear, reproducible code. I can begin working on this immediately and am available to communicate in real-time according to your time zone. I can also deliver a portion of the project or a simple demo within 12 hours of starting. Q1: What specific format do you need for the results table? Q2: Are there any particular standards or guidelines you would like to follow for the ROC curve presentation? Q3: Would you prefer to receive the code in Jupyter Notebook, R script, or another format? Looking forward to your response. Best regards, Everett

@jovans38

Hi there, I can extract your pooled diagnostic metrics directly from your Excel dataset, perform a meta-analytic pooling of sensitivity and specificity, and deliver clear, auditable outputs. I’ll implement a reproducible workflow in Python (pandas + statsmodels) or R (dmetar/mada) depending on your preference, with transparent steps and a plotted ROC curve that includes the area under the curve and 95% confidence intervals. Your deliverables will include: - A concise results table with pooled sensitivity, specificity, and 95% CIs. - The ROC curve image plus the underlying coordinates (thresholds, TPR, FPR). - Reproducible code or a notebook with commented steps to audit or update later. Workflow outline: 1) Load data from Excel, validate columns for true positives/negatives and test results. 2) Compute study-level sensitivities/specificities and perform a random-effects meta-analysis for pooling. 3) Generate 95% CIs and create a ROC curve with coordinates. 4) Output the results in a shareable format and provide step-by-step instructions to reproduce. Best regards,

@dmytrom99pro

Hello, As a seasoned data scientist with a strong command of Python, I am highly experienced in working with precisely the kind of data processing and analyses you require. With your Excel spreadsheet as the starting point, I am well-versed in writing reproducible and clearly documented steps using Python to generate your desired outputs. My familiarity with packages such as scikit-learn positions me uniquely for this job. My profound knowledge of statistics and data visualization, complemented by my skills in Python will yield tangible results for you. I ensure top-notch quality, which you can always depend on. Furthermore, I don't just 'deliver code' - I deliver complete systems that have zero technical debt and are built to scale optimally. To sum it up, my expertise in data handling combined with my experience in real-time systems will undeniably be an asset to your project. Given a reasonable time frame, I commit to not only producing insightful results but also handing over meticulous codes and detailed documentation for future references or updates. Let's discuss how we could make your vision into a robust reality together! Thanks!