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Related Concept Videos

Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
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Decision Making: P-value Method01:09

Decision Making: P-value Method

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
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Design Consideration01:22

Design Consideration

363
Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Updated: Oct 13, 2025

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
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A Two-Stage Decision Making Approach for Safety Studies.

Jessica Kim1, Zhipeng Huang1

  • 1Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Science, Office of Biostatistics, Division of Biometrics VIII and Division of Biometrics I, Silver Spring, Maryland, USA.

Journal of Biopharmaceutical Statistics
|November 15, 2021
PubMed
Summary
This summary is machine-generated.

Statistical non-significance in safety studies can be misinterpreted. The proposed Two-Stage Decision-Making (TSDM) approach enhances safety study design by integrating signal detection and concern ruling-out criteria for clearer conclusions.

Keywords:
Detecting a safety signalMonte Carlo simulationsalpha spending functionconfidence intervalgroup sequential designoperational type I errorruling out a safety concernstudy powertwo-stage decision-making (TSDM) approach

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Area of Science:

  • Pharmacovigilance and Drug Safety
  • Biostatistics and Clinical Trial Design

Background:

  • Traditional safety studies often use hypothesis testing for detecting safety signals or ruling out concerns, but non-significant results can be ambiguous.
  • Misinterpreting non-significance as absence of risk is problematic, especially with low power or high variability in safety data.
  • Existing frameworks may not adequately combine the objectives of detecting potential harm and confirming safety.

Purpose of the Study:

  • To introduce a novel Two-Stage Decision-Making (TSDM) approach for safety studies to address interpretation issues with non-significant findings.
  • To enhance the probability of reaching a definitive conclusion in safety assessments by integrating both signal detection and risk-ruling-out objectives.
  • To provide a robust statistical framework for safety studies that improves decision-making clarity.

Main Methods:

  • The TSDM approach is a ruling-out design incorporating an interim analysis.
  • It applies both detecting and ruling-out criteria at interim and final stages using a pre-specified alpha spending function.
  • The framework utilizes both directions of the confidence interval for decision-making at each analysis stage.

Main Results:

  • The TSDM approach was assessed for operational type I error rate, overall study power, and probability of making a decision.
  • Monte Carlo simulations were conducted to evaluate the approach's properties across various confidence interval outcome types.
  • The study provides insights into sample size requirements and statistical interpretations for the TSDM design.

Conclusions:

  • The proposed Two-Stage Decision-Making (TSDM) approach offers a unified framework for safety studies, improving the ability to detect safety signals and rule out concerns.
  • This integrated design increases the likelihood of making a definite decision, thereby enhancing the reliability of safety assessments.
  • The TSDM approach has significant implications for optimizing clinical trial design in drug safety evaluations.