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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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, controlled...
Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Drug Dosing in Renal Diseases: Dose Adjustments Based on Drug Clearance and Elimination Rate Constant01:25

Drug Dosing in Renal Diseases: Dose Adjustments Based on Drug Clearance and Elimination Rate Constant

In patients with renal disease, dosage adjustments are necessary to maintain therapeutic plasma drug concentrations and prevent toxicity or subtherapeutic exposure. Renal impairment alters drug pharmacokinetics, especially in conditions like uremia, where changes such as prolonged elimination half-life and altered apparent volume of distribution can significantly affect drug disposition. These changes require careful modification of the dosing regimen to achieve the desired clinical...

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Sample size re-estimation in clinical trials.

Michael A Proschan1

  • 1National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892-7609, USA. ProschaM@mail.nih.gov

Biometrical Journal. Biometrische Zeitschrift
|April 10, 2009
PubMed
Summary
This summary is machine-generated.

Adaptive clinical trials offer flexibility but face mistrust due to potential extreme results. This review examines flexible sample size re-estimation methods for continuous outcomes, highlighting advantages and disadvantages.

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Area of Science:

  • Biostatistics
  • Clinical Trial Design

Background:

  • Adaptive clinical trials are increasingly utilized for their inherent flexibility.
  • These trials allow modifications to sample size, endpoints, and populations mid-study.
  • However, adaptive designs face skepticism regarding their performance in extreme scenarios.

Purpose of the Study:

  • To review flexible statistical methods for sample size re-estimation in adaptive clinical trials.
  • To provide a comprehensive understanding of the benefits and drawbacks of these evolving methodologies.

Main Methods:

  • Literature review of adaptive clinical trial methodologies.
  • Focus on statistical approaches for sample size re-estimation with continuous outcomes.

Main Results:

  • Adaptive trials offer significant design flexibility.
  • Potential for "bizarre" or unreliable results in extreme settings requires careful consideration.
  • Sample size re-estimation methods are crucial for maintaining trial integrity.

Conclusions:

  • Understanding the trade-offs of adaptive trials is essential for researchers.
  • Flexible sample size re-estimation is a key component in managing adaptive trial complexities.
  • Further research is needed to address concerns about extreme settings.