Related Experiment Video
Updated: Sep 5, 2025
08:33
A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
Published on: September 4, 2019
7.1K
The cross-over of statistical thinking and practices: A pandemic catalyst
1Scientific Operations, ICON Clinical Research UK, Reading, UK.
Pharmaceutical Statistics
|July 12, 2022
Summary
Statistical thinking should bridge drug development, public health, and social science. Embedding experimental frameworks post-authorization and using data standards can improve interventions and treatments.
Area of Science:
- Statistics
- Public Health
- Drug Development
- Social Science
Background:
- The COVID-19 pandemic highlighted the need for robust statistical practices.
- Traditional disciplinary boundaries can limit the application of effective statistical thinking.
- Andy Grieve's work exemplifies interdisciplinary statistical application.
Purpose of the Study:
- To advocate for the integration of statistical thinking across diverse scientific fields.
- To propose enhanced frameworks for evaluating interventions and treatments post-authorization.
- To encourage greater adoption of data standards in public health and social science research.
Main Methods:
- Review of statistical practices in drug development, public health, and social science.
- Argument for adopting experimental or quasi-experimental designs in clinical practice.
- Emphasis on pre-specification of effect sizes and data standardization for public health interventions.
Main Results:
- Statistical thinking offers significant potential when applied beyond traditional disciplinary silos.
- Implementing experimental frameworks in post-authorization settings can yield more reliable evidence.
- Standardized data and pre-specified outcomes enhance the evaluation of public health initiatives.
Conclusions:
- There is a compelling need to integrate statistical methodologies across drug development, public health, and social science.
- Adopting rigorous, pre-specified evaluation frameworks is crucial for improving interventions and treatments.
- While progress is noted, further efforts are required to fully embed these advanced statistical practices.
Keywords:
COVID-19NPIsmaster protocolspharmacovigilanceregression discontinuity designstepped-wedge cluster randomisation designvaccinesMore Related Videos
Related Concept Videos
01:18Steps in Outbreak Investigation
181
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
181
01:25Statistical Methods for Analyzing Epidemiological Data
511
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
511
01:21Causality in Epidemiology
752
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
752
01:16Crossover Experiments
2.9K
Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
2.9K
01:16Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
195
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
195
01:15Study Design in Statistics
8.4K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
8.4K