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Related Concept Videos

Clinical Trials01:16

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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...
Clinical Trials: Overview01:11

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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...
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
Central Limit Theorem01:14

Central Limit Theorem

The central limit theorem, abbreviated as clt, is one of the most powerful and useful ideas in all of statistics. The central limit theorem for sample means says that if you repeatedly draw samples of a given size and calculate their means, and create a histogram of those means, then the resulting histogram will tend to have an approximate normal bell shape. In other words, as sample sizes increase, the distribution of means follows the normal distribution more closely.
The sample size, n, that...

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Revisiting sample size: are big trials the answer?

Giovanna A L Lurati Buse1, Fernando Botto, P J Devereaux

  • 1Population Health Research Institute, Hamilton Health Sciences, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada.

The Journal of Bone and Joint Surgery. American Volume
|July 20, 2012
PubMed
Summary
This summary is machine-generated.

Randomized controlled trials (RCTs) require rigorous design and adequate sample size for reliable evidence. This review highlights sample size estimation pitfalls and the importance of large trials in orthopaedic research.

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Area of Science:

  • Orthopaedic Surgery
  • Clinical Trials Methodology
  • Biostatistics

Background:

  • Randomized controlled trials (RCTs) are crucial for high-quality medical evidence.
  • Evidence quality in RCTs depends on design, implementation, and statistical power.
  • Orthopaedic research often suffers from underpowered RCTs due to small sample sizes.

Purpose of the Study:

  • To review fundamental concepts and common errors in sample size estimation for clinical trials.
  • To emphasize the critical role of adequate sample size in ensuring the validity of orthopaedic RCTs.
  • To advocate for the use of large-scale trials to generate robust evidence in orthopaedics.

Main Methods:

  • Review of key principles in sample size calculation and statistical power.
  • Discussion of potential biases arising from inadequate sample sizes in RCTs.
  • Analysis of the impact of sample size on the reliability of treatment effect estimates.

Main Results:

  • Proper randomization, allocation concealment, and intention-to-treat analysis are essential for RCT validity.
  • Statistical power, directly influenced by sample size, is a critical determinant of RCT quality.
  • Insufficient sample sizes in orthopaedic RCTs frequently compromise the reliability of findings.

Conclusions:

  • Accurate sample size estimation is paramount for conducting high-quality orthopaedic RCTs.
  • Large, well-powered trials are necessary to generate valid and generalizable evidence in orthopaedic surgery.
  • Addressing sample size limitations is crucial for advancing evidence-based orthopaedic practice.