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Related Concept Videos

Convenience Sampling Method00:55

Convenience 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.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Sample Proportion and Population Proportion01:20

Sample Proportion and Population Proportion

Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
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...
Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure 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.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...

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Updated: Jun 6, 2026

Mapping Infant Immunity with Minimal Input: Integrative Single-Cell and Multiomic Profiling
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Is a 'convenience' sample useful for estimating immunization coverage in a small population?

Jean E Weir1, Carrie Jones

  • 1SIL Clinic, Ukarumpa, Papua New Guinea.

Papua and New Guinea Medical Journal
|November 11, 2010
PubMed
Summary
This summary is machine-generated.

Convenience sampling for immunization coverage in Papua New Guinea showed accuracy within 10% of true rates in specific scenarios. This rapid survey method can be useful for identifying areas with low vaccine coverage.

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Area of Science:

  • Public Health
  • Epidemiology
  • Global Health

Background:

  • Rapid survey methodologies are crucial for assessing immunization coverage in developing nations.
  • Non-random convenience sampling is generally not preferred for coverage estimation due to potential bias, despite its cost-effectiveness and speed.

Purpose of the Study:

  • To evaluate the accuracy of convenience sampling for estimating immunization coverage.
  • To compare coverage rates from a convenience sample with true coverage data in rural Papua New Guinea.

Main Methods:

  • A convenience sample of children attending a travelling clinic was compared to a complete survey of all children in three villages.
  • Immunization coverage rates (specifically Diphtheria-Tetanus-Full) were calculated for both sampling methods.

Main Results:

  • Convenience sampling estimated coverage within 10% of the true rate when the sample represented two-thirds of children or included only those over one year old.
  • Discrepancies of 11% were observed when the convenience sample represented 53% of children or included all eligible children.

Conclusions:

  • Convenience sampling may provide sufficiently accurate immunization coverage estimates for reporting purposes.
  • This rapid assessment method is valuable for identifying regions with suboptimal vaccine uptake.