Quantzig, a leader in delivering scalable analytics solutions and data science services, today announced the completion of its recent article that offers comprehensive insights into the role of propensity score matching in clinical research.
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Propensity score matching enables researchers to accurately gauge the impact of treatments or new therapies, which may otherwise be deemed invalid due to the imbalance between treatment groups. (Graphic: Business Wire)
The insights obtained through propensity score modeling are opening up new opportunities that enable businesses to improve customer retention, enhance marketing campaigns, minimize risks, and reduce spend while driving decision-making. Request a FREE proposal to learn more.
Propensity score matching (PSM) is a widely used statistical method that leverages the power of natural language processing, statistics, and data science to generate meaningful insights by connecting thousands of data points. In the field of clinical research, propensity score matching finds numerous use cases. Though the growing use case for propensity analysis in this field can be attributed to several factors, the primary reason revolves around the availability of huge volumes of randomized, unstructured clinical data.
Quantzig conducted a deep-dive analysis to understand the role of propensity analysis in the clinical research sector. Based on the outcome, Quantzig was able to understand better its advantages, limitations, and applications, each of which is listed in the article. Read the complete article here: https://bit.ly/2OKEqiW
- Comprehensive insights into the role of propensity score matching in clinical research
- Learn why propensity analysis is the need of the hour in clinical research studies
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Quantzig’s deep domain expertise in the field of analytics has helped them understand the uniqueness of businesses, especially when it comes to analyzing propensity scores. Based on its expertise, Quantzig has developed a comprehensive suite of solutions that revolve around propensity score modeling and score matching to derive accurate conclusions. By leveraging propensity analysis, those involved in the process of drug efficacy evaluation or treatment analysis are likely to spend less time and resources in making assumptions and can instead rely on insights to take prompt actions.
“The successful implementation of propensity score models is deep-rooted and depends on the use of efficient data acquisition strategies, availability of high-quality data, and an impactful use case,” says an advanced analytics expert at Quantzig.
Speak to our experts to learn how we can help you create a dynamic, scalable propensity score model that is capable of demonstrating ROI in the long run.
Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. For more than 15 years, we have assisted our clients across the globe with end-to-end data modeling capabilities to leverage analytics for prudent decision making. Today, our firm consists of 120+ clients, including 45 Fortune 500 companies. For more information on our engagement policies and pricing plans, visit: https://www.quantzig.com/request-for-proposal