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Related Concept Videos

Statistical Significance01:37

Statistical Significance

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
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...
Significance Testing: Overview01:04

Significance Testing: Overview

Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
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...
Statistical Hypothesis Testing01:16

Statistical Hypothesis Testing

Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
Bioequivalence Data: Statistical Interpretation01:16

Bioequivalence Data: Statistical Interpretation

The statistical interpretation of bioequivalence data is a significant aspect of pharmaceutical research. Bioequivalence refers to the absence of any significant difference in the rate and extent to which the active ingredient in pharmaceutical products becomes available at the site of drug action when administered at the same molar dose under similar conditions. This helps determine if different drug products have similar absorption rates, ensuring their interchangeability.Statistical...

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Related Experiment Video

Updated: May 29, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials
08:36

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

Published on: April 19, 2024

Statistical significance testing and clinical effectiveness studies.

Edward A Wise1

  • 1Mental Health Resources, Memphis, TN 38119, USA. edwisephd@gmail.com

Psychotherapy (Chicago, Ill.)
|August 31, 2011
PubMed
Summary
This summary is machine-generated.

Effectiveness studies can identify patient and treatment variables in real-world practice. Clinically significant and reliable change indices help demonstrate patient progress using diverse outcome variables.

Related Experiment Videos

Last Updated: May 29, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials
08:36

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

Published on: April 19, 2024

Area of Science:

  • Clinical Psychology
  • Health Services Research

Background:

  • Effectiveness studies require real-world patient and treatment variables.
  • Identifying covariates influencing outcomes is crucial for accurate assessment.

Purpose of the Study:

  • To review the use of clinically significant change and reliable change indices.
  • To demonstrate patient change based on normative comparisons using diverse outcome variables.
  • To address limitations in randomized trials regarding covariates and file-drawer effects.

Main Methods:

  • Review of clinically significant change and reliable change indices.
  • Analysis of outcome relevant variables reflecting diverse client problems.
  • Individual-level analysis of treatment response in 'treatment as usual' studies.

Main Results:

  • Clinically significant and reliable change indices allow for normative comparisons.
  • Diverse outcome variables can reflect a wide range of client concerns.
  • Individual-level analysis can identify clinically relevant outcomes even without controlled covariates.

Conclusions:

  • Agreement on a single outcome index or plotting entire distributions is not necessary.
  • Existing methods can address limitations of randomized trials.
  • Studying individual treatment response can identify clinically relevant variables and guide treatment adjustments.