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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...
Random Sampling Method01:09

Random Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Systematic Sampling Method01:17

Systematic Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
Study Design in Statistics01:15

Study Design in Statistics

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...

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Related Experiment Video

Updated: Jun 30, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Sample size determination for bibliographic retrieval studies.

Xiaomei Yao1, Nancy L Wilczynski, Stephen D Walter

  • 1Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada. yaoxia@mcmaster.ca

BMC Medical Informatics and Decision Making
|October 1, 2008
PubMed
Summary
This summary is machine-generated.

Randomly sampling journals efficiently updates MEDLINE search strategies for high-quality therapy articles. This method requires sufficient high-quality articles but is less effective for diagnosis and prognosis studies due to low article concentrations.

Related Experiment Videos

Last Updated: Jun 30, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Area of Science:

  • Medical Informatics
  • Information Retrieval
  • Evidence-Based Medicine

Background:

  • Developing effective search strategies for high-quality clinical articles in MEDLINE is resource-intensive.
  • Existing search strategies require frequent updates to maintain accuracy and relevance.
  • This study addresses the challenge of efficiently updating and creating MEDLINE search strategies.

Purpose of the Study:

  • To determine the minimum number of high-quality articles needed in a journal subset for updating MEDLINE search strategies.
  • To evaluate the efficacy of different journal subset selection approaches (random sampling vs. top journals) for strategy development.
  • To assess the performance of newly derived search strategies across different journal subsets and study types (treatment, diagnosis, prognosis).

Main Methods:

  • Calculated the required number of high-quality articles based on desired confidence interval width (W) for search strategy sensitivity.
  • Derived new search strategies using two journal subset approaches: random sampling and selecting top-yielding journals.
  • Tested the performance of new strategies in both a comprehensive journal database and a low-yielding subset.

Main Results:

  • For treatment studies, 15 randomly sampled journals or 2 top journals (with ≥99 high-quality articles) adequately updated existing search strategies.
  • Strategies developed from random sampling performed better in low-yielding subsets compared to the top journal approach.
  • No journal subset contained sufficient high-quality articles to meet the target confidence interval width for diagnosis and prognosis studies.

Conclusions:

  • Randomly sampling a small, high-quality article-rich journal subset is an efficient method for updating MEDLINE search strategies for therapy literature.
  • The concentration of high-quality diagnosis and prognosis articles is too low for this random sampling approach to be effective.
  • This research offers a practical approach to optimize MEDLINE search strategy development for specific clinical areas.