Sampling in Quantitative Research

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Questions and Answers

What characteristics must children possess to be eligible for the study?

They must be between 8 and 14 years.

They must be aged 6 to 12 years.

They must be healthy and aged 7 to 14 years. (correct)

They must have a minor medical condition.

Which of the following is NOT a reason for the importance of sampling in quantitative research?

Generalizability of findings.

Descriptive accuracy. (correct)

Minimized bias.

Cost-effectiveness.

What is a significant feature of probability sampling?

It requires the researchers to know all population characteristics.

It introduces bias due to non-random selection.

Every element has an equal chance of being selected. (correct)

Elements are chosen based on convenience.

Which of the following describes convenience sampling?

Involves selecting the most easily available participants. Signup and view all the answers

What is the goal of designing a sampling plan?

To create a sample that reflects the population's traits. Signup and view all the answers

What is a potential drawback of nonprobability sampling?

It can introduce bias in the results. Signup and view all the answers

Which type of sampling allows researchers to apply findings from the sample to the entire population?

Random sampling. Signup and view all the answers

Why is careful sampling important in research?

It minimizes bias and improves the validity of results. Signup and view all the answers

What is the primary purpose of Cochran's formula in survey research?

To ensure the sample size is large enough for reliable results. Signup and view all the answers

What is the confidence level commonly used in Cochran's formula?

95% Signup and view all the answers

If the actual population proportion is unknown, what value should be used for p in Cochran's formula?

0.5 Signup and view all the answers

What is the margin of error if the desired level is set at 5%?

0.05 Signup and view all the answers

For a large population, what is the sample size needed for a confidence level of 95% and a 5% margin of error?

384 respondents Signup and view all the answers

Which step is NOT part of the Cochran's formula process?

Estimate the population variance. Signup and view all the answers

What does using a p value of 0.5 in Cochran's formula achieve?

Maximizes the required sample size. Signup and view all the answers

What is the Z-value corresponding to a 95% confidence level?

1.96 Signup and view all the answers

What is meant by data saturation in qualitative research?

The point where new information stops appearing in the data. Signup and view all the answers

How many participants are typically involved in phenomenological studies?

5-10 participants Signup and view all the answers

Which qualitative research method typically requires the largest sample size?

Grounded Theory Signup and view all the answers

Why is managing sample size important in qualitative research?

To facilitate deep data analysis and collection. Signup and view all the answers

What influences sample size decisions in qualitative research?

Resources such as time and budget. Signup and view all the answers

In ethnography, how does the number of participants typically vary?

It usually studies a small number intensively over time. Signup and view all the answers

What is a primary focus of qualitative research?

To understand the mechanisms behind phenomena. Signup and view all the answers

In a case study approach, what range of cases might typically be analyzed?

1-5 cases for intensive detail. Signup and view all the answers

What is the primary goal of stratified random sampling?

To enhance representativeness Signup and view all the answers

In systematic sampling, how is a sample selected from a list?

By selecting every nth case from a predetermined starting point Signup and view all the answers

What factor does NOT influence sample size determination?

Study location Signup and view all the answers

A common margin of error used in sample size determination is:

0.05 or 5% Signup and view all the answers

What is represented by a Z-value of 1.96 in statistical formulas?

Confidence level of 95% Signup and view all the answers

Which sampling method involves dividing the population into groups before sampling?

Stratified Sampling Signup and view all the answers

What is a common practice if the variance in a population is unknown?

Use a variance of 50% for conservative estimates Signup and view all the answers

What sample size was achieved by Ridout and colleagues using systematic sampling?

294 cases Signup and view all the answers

What is the main purpose of quota sampling?

To ensure representation of specific subgroups in a sample Signup and view all the answers

Which type of sampling involves recruiting all individuals over a specific time period?

Consecutive Sampling Signup and view all the answers

In purposive sampling, how are sample members chosen?

Based on predetermined eligibility criteria Signup and view all the answers

What is the main characteristic of snowball sampling?

Early sample members refer other individuals for inclusion Signup and view all the answers

Which statement best describes simple random sampling?

It requires a sampling frame to randomly select participants Signup and view all the answers

In the study conducted by Neta et al. (2015), what was the primary focus population?

Patients with type 2 diabetes mellitus Signup and view all the answers

Which of the following is NOT considered a form of nonprobability sampling?

Simple Random Sampling Signup and view all the answers

What is a characteristic feature of a sampling frame?

It is a list of every member of the population being studied Signup and view all the answers

Study Notes

Inclusion and Exclusion Criteria

Children participating in a study must be healthy and between 7 and 14 years old.
Children with major medical illnesses, such as diabetes, heart disease, or asthma, are excluded.

Sampling

Sampling involves selecting a subset of the population to represent it.
A sampling plan specifies how the sample will be selected and how many subjects will participate.
The goal of sampling is to have a sample that adequately reflects the population's characteristics.

Importance of Sampling in Quantitative Research

Generalizability: Well-designed samples allow findings to be applied to the entire population.
Cost-Effectiveness: Sampling is more practical and cost-effective than studying the entire population.
Accuracy: Careful sampling minimizes bias, improving the validity of research results.

Sampling Designs

Nonprobability Sampling: Sample elements are selected by nonrandom methods, where every element doesn't have an equal chance of being included. Can introduce bias, but sometimes used for exploratory research.
Probability Sampling: Involves random selection of elements from a population. Each element has an equal, independent chance of being selected. Reduces bias and increases generalizability.

Nonprobability Sampling Designs

Convenience Sampling: Selecting the most conveniently available people as participants. Weakest form of sampling, but commonly used.
Quota Sampling: Researchers identify population strata and figure out how many people are needed from each stratum. Aims to mirror the population's proportions.
Consecutive Sampling: Recruiting all people from an accessible population over a specific time interval or for a specified sample size.
Purposive Sampling: Researchers handpick sample members based on their knowledge of the population.
Snowball Sampling: Early participants identify and refer other people who meet the eligibility criteria.

Probability Sampling Designs

Simple Random Sampling: The most basic of the probability sampling plans. Elements are randomly selected from a sampling frame.
Stratified Random Sampling: The population is divided into two or more strata, from which elements are randomly selected.
Systematic Sampling: Selection of every nth case from a list, such as every 10th person on a patient list.

Sample Size - Quantitative

The sample size depends on:
- Population Size: Larger populations generally require larger samples.
- Margin of Error: How much error is acceptable (smaller margins require larger samples).
- Confidence Level: Usually 95%, represented by a Z-value of 1.96.
- Variance: Variability within the population. A 50% variance is often used for conservative estimates.

Cochran Formula

Commonly used in survey research, especially when sampling a large population.
Ensures a sample size that provides reliable, statistically significant results.
Steps:
1. Set the confidence level (usually 95%).
2. Estimate the population proportion (p).
3. Determine the margin of error (e).
4. Plug these values into the formula to calculate the required sample size.

Sample Size - Qualitative

Sample size in qualitative research seeks to understand how and why things happen, rather than quantifying outcomes.

Key Considerations for Sample Size in Qualitative Research:

Purpose of the Study: The sample size should be large enough to ensure data saturation but small enough to manage the depth of analysis required.
Data Saturation: Saturation is reached when no new information or themes are emerging from the data.

Sample Size for Different Qualitative Research Approaches:

Phenomenology: Often involves 5-10 participants, focusing on deep exploration.
Grounded Theory: May require 20-30 participants or more, as it aims to develop a theory from the data.
Ethnography: Can vary greatly but usually fewer participants are studied intensively over a long period.
Case Study: A single case study might focus on 1-5 cases, with detailed analysis of each case.

Pragmatic Considerations in Qualitative Sampling:

Resources (time, budget, and availability of participants) often influence sample size decisions.
Small, manageable sample sizes are often used in qualitative research due to the intensive nature of data collection and analysis.

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Description

Explore the fundamental concepts of sampling in quantitative research. This quiz covers inclusion and exclusion criteria, sampling methods, and the importance of effective sampling designs. Test your understanding of how sampling impacts research validity and generalizability.