Randomly selecting a proportionate amount from subgroups is an example of what?

UPUMS Nsg.Officer-2024

Nursing Research & Statistics

Easy

Appeared in: UPUMS Nsg.Officer-2024

Explanation

Stratified sampling involves dividing a heterogeneous population into smaller, homogeneous subgroups called strata.
The strata are based on shared characteristics like age, gender, or diagnosis.
After stratification, subjects are randomly selected from each subgroup in a number that is proportional to the subgroup's size relative to the total population.
This method ensures that all subgroups are adequately represented in the final sample, improving the accuracy and generalizability of the research findings.

Option A: Convenience sampling is a non-probability method that relies on selecting individuals who are easily accessible. It does not involve creating subgroups or ensuring proportionate representation.
Option C: Systematic sampling involves selecting every 'kth' subject from a population list. It does not involve dividing the population into subgroups first.
Option D: Simple random sampling involves selecting subjects from the entire population as a whole, where every individual has an equal chance of being chosen. It does not categorize the population into subgroups before sampling.

Clinical Relevance

Nursing practice connection: This is primarily an exam-oriented knowledge point with limited direct bedside application, so retain Probability sampling techniques in research methodology as background academic context rather than a clinical decision trigger.
In nursing research, stratified sampling is crucial for ensuring that studies on diverse patient populations are accurate. For example, when studying the effectiveness of a new diabetes management program, a researcher can stratify the population by age groups (e.g., young adults, middle-aged, elderly) to ensure each group's response is adequately captured.
This method allows for comparisons between different subgroups, such as evaluating if a health intervention is more effective in urban versus rural patients.
What if? - If a researcher used simple random sampling instead of stratified sampling in a study of a nursing intervention across different hospital units (ICU, pediatrics, general ward), they might, by chance, get too many participants from one unit and too few from another. This would make it difficult to generalize the findings to all units.

How to Approach the Question

First, analyze the question stem to identify the key defining phrases.
The keywords are 'subgroups' and 'proportionate amount'.
Recall the definitions of the different sampling techniques provided in the options.
Recognize that in research terminology, 'subgroups' are referred to as 'strata'.
Match the process described—dividing into subgroups and then selecting a proportionate amount—with its correct term, which is Stratified Sampling.

Concept Tested & Keywords

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E6 NursingResearch Suresh Sharma 5e Part 1 p. 238-240

E6 NursingResearch Sukhpal Kaur p. 254-256