Sampling Methods — MCQs
The population is divided into homogeneous subgroups, and then individuals are randomly selected from each subgroup. What type of sampling is this?
A study was conducted to investigate the relationship between COPD and smoking. Data was collected from government hospital records on COPD cases and cigarette sales records from finance and taxation departments. What is the study design?
Recall bias is most commonly associated with which study design?
Admission rate bias is?
Which of the following is the MOST important vital statistic in a population?
What is the type of sampling used when a random sample is taken from distinct groups within a population, such as religious groups like Hindus, Muslims, and Christians?
Which of the following is not a method of random sampling?
This is a map of an urban slum in New Delhi. The medical officer of PHC notified the higher authorities on observing multiple cases of measles in 1-2 years age group. The authorities conducted a survey of vaccine coverage in the area in the manner shown below. Which sampling is depicted here?
Which of the following is a non-probability sampling method?
In a village, every fifth house was selected for a study. This is an example of
Sampling Methods Indian Medical PG Practice Questions and MCQs
Question 1: The population is divided into homogeneous subgroups, and then individuals are randomly selected from each subgroup. What type of sampling is this?
- A. Simple random
- B. Stratified random (Correct Answer)
- C. Cluster
- D. Systematic random
Explanation: ***Stratified random*** - In **stratified random sampling**, the population is first divided into homogeneous subgroups (strata), and then a simple random sample is drawn from each stratum. - This method ensures representation from all subgroups, which is implied by the description "separated into groups, from each group people are selected randomly." *Simple random* - **Simple random sampling** involves selecting individuals from an entire population purely by chance, where each individual has an equal probability of being chosen. - This method does not involve an initial division of the population into distinct groups before selection. *Systematic random* - **Systematic random sampling** involves selecting every nth individual from a list after a random starting point. - This method does not involve dividing the population into groups and then sampling from each group. *Cluster* - **Cluster sampling** involves dividing the population into clusters (usually naturally occurring groups), randomly selecting a few clusters, and then sampling *all* individuals within the selected clusters. - In cluster sampling, individuals are not randomly selected *from each* group; instead, entire groups are selected.
Question 2: A study was conducted to investigate the relationship between COPD and smoking. Data was collected from government hospital records on COPD cases and cigarette sales records from finance and taxation departments. What is the study design?
- A. Cross-sectional study
- B. Operational study
- C. Case-control study
- D. Ecological study (Correct Answer)
Explanation: ***Ecological study*** - This study uses **aggregate data** (COPD cases from hospital records, cigarette sales from taxation departments) at the population level, not individual data. - It investigates the relationship between exposure (smoking) and outcome (COPD) across different populations or groups. *Cross-sectional study* - A **cross-sectional study** collects data on exposure and outcome at a **single point in time** from individuals, which is not the case here as aggregate data is used. - It describes the prevalence of a disease and exposure in a population, but does not examine the relationship using population-level aggregates. *Operational study* - An **operational study** focuses on evaluating the effectiveness and efficiency of health services or programs in real-world settings. - It typically involves assessing how well interventions are implemented and their impact, rather than investigating the relationship between disease and exposure using aggregate data. *Case-control study* - A **case-control study** compares individuals with a disease (cases) to individuals without the disease (controls) and looks back retrospectively to identify exposures. - This design relies on individual-level data and is not suitable when only population-level aggregate data is available.
Question 3: Recall bias is most commonly associated with which study design?
- A. Case control (Correct Answer)
- B. RCT
- C. Field trial
- D. Cohort
Explanation: ***Case control*** - **Recall bias** is a significant concern in **case-control studies** because participants are asked to remember past exposures, and those with the disease (cases) may recall exposures differently or more thoroughly than healthy controls. - This differential recall can lead to an artificial association between an exposure and the outcome, even if no true association exists. *Cohort* - **Cohort studies** generally have a lower risk of recall bias because exposure information is collected **prospectively, before the outcome occurs**. - While some recall may be involved in initial exposure assessment, it is less susceptible to differential recall influenced by disease status compared to case-control studies. *RCT* - **Randomized controlled trials (RCTs)** are the least susceptible to recall bias because they involve **prospective data collection** and intervention assignment. - Exposure (intervention) is assigned by the researchers, and outcomes are measured systematically, minimizing reliance on participants' retrospective recall of exposures. *Field trial* - **Field trials** are a type of **intervention study** conducted in a natural setting and are generally less prone to recall bias than case-control studies, similar to RCTs. - Exposure is typically assigned or observed prospectively, and outcomes are measured systematically, reducing the impact of participant recall on exposure status.
Question 4: Admission rate bias is?
- A. Reporting bias
- B. Response bias
- C. Berksonian bias (Correct Answer)
- D. None of the options
Explanation: ***Berksonian bias*** - **Berksonian bias** is a form of selection bias, also known as **admission rate bias**, that occurs when different rates of admission to a hospital or clinical setting distort the association between diseases or between a disease and a risk factor. - This bias arises because the hospitalized population may not be representative of the general population, leading to spurious associations or masking real ones. *Reporting bias* - **Reporting bias** is a type of information bias where the outcome or exposure information is reported inaccurately, often due to social desirability or recall issues. - It does not specifically refer to distortions stemming from hospital admission rates. *Response bias* - **Response bias** occurs when participants in a study alter their answers or behavior from what is true due to factors like leading questions, social desirability, or acquiescence. - This is an issue related to data collection, not an unrepresentative study population due to hospital admission protocols. *None of the options* - Berksonian bias directly corresponds to the definition of admission rate bias, making this option incorrect.
Question 5: Which of the following is the MOST important vital statistic in a population?
- A. Fertility rate
- B. Morbidity rate
- C. Birth rate
- D. Mortality rate (Correct Answer)
Explanation: ***Mortality rate*** - The **mortality rate** directly reflects the health status and overall well-being of a population by indicating the number of deaths per unit population. - A high mortality rate signals underlying public health issues, inadequate healthcare, or poor living conditions, making it the **most critical vital statistic** for assessing population health and guiding interventions. - It serves as a **key indicator** for comparing health status across populations and time periods. *Fertility rate* - The **fertility rate** measures the average number of children born to women of reproductive age, influencing future population size and age structure. - While important for demographic planning and population projections, it doesn't directly provide insights into the immediate health challenges or mortality burden of a population. *Morbidity rate* - The **morbidity rate** quantifies the incidence or prevalence of disease in a population, reflecting the disease burden. - Although crucial for understanding health problems and planning healthcare services, it is considered secondary to mortality as a vital statistic since mortality represents the ultimate health outcome. *Birth rate* - The **birth rate** quantifies the number of live births per 1,000 people in a year, contributing to population growth and demographic trends. - Like the fertility rate, it is essential for understanding natality patterns but offers less insight into the overall health status and survival of a population compared to the mortality rate.
Question 6: What is the type of sampling used when a random sample is taken from distinct groups within a population, such as religious groups like Hindus, Muslims, and Christians?
- A. Simple random
- B. Stratified random (Correct Answer)
- C. Cluster
- D. Systematic random
Explanation: ***Stratified random*** - This method involves dividing the population into **distinct, non-overlapping subgroups (strata)** based on a shared characteristic (e.g., religious groups). - A **random sample** is then drawn from each stratum, ensuring representation from all groups. *Simple random* - Involves selecting individuals entirely at **random** from the entire population, with each individual having an equal chance of being chosen. - It does not guarantee representation from specific subgroups within the population. *Systematic random* - This method selects individuals at **regular intervals** from a randomly ordered list of the population (e.g., every 10th person). - While it offers a degree of randomness, it does not specifically account for or ensure representation of distinct subgroups. *Cluster* - This method involves dividing the population into **clusters (natural groupings)**, usually geographically, and then randomly selecting entire clusters to sample. - Unlike stratified sampling, where individuals are selected from each stratum, cluster sampling involves sampling all individuals within chosen clusters.
Question 7: Which of the following is not a method of random sampling?
- A. Cluster sampling
- B. Stratified sampling
- C. Simple random
- D. Quota sampling (Correct Answer)
Explanation: ***Quota sampling*** - **Quota sampling** is a non-probability sampling method where researchers select a sample based on pre-defined characteristics to match the population's proportions. - It does not involve random selection at any stage, making it a non-random sampling technique. *Cluster sampling* - **Cluster sampling** is a probability (random) sampling technique where the population is divided into clusters, and then a random sample of these clusters is selected. - All units within the selected clusters are then included in the sample, or a random sample is taken from within the selected clusters. *Stratified sampling* - **Stratified sampling** is a probability (random) sampling method that involves dividing the population into homogeneous subgroups (strata) and then taking a random sample from each stratum. - This method ensures representation from all important subgroups within the population. *Simple random* - **Simple random sampling** is a basic probability (random) sampling technique where every member of the population has an equal chance of being selected for the sample. - This method is considered the most fundamental type of random sampling.
Question 8: This is a map of an urban slum in New Delhi. The medical officer of PHC notified the higher authorities on observing multiple cases of measles in 1-2 years age group. The authorities conducted a survey of vaccine coverage in the area in the manner shown below. Which sampling is depicted here?
- A. Simple random sampling
- B. Systematic random sampling
- C. Stratified random sampling
- D. Cluster sampling (Correct Answer)
Explanation: ***Cluster sampling*** - The image shows **groups (clusters)** of houses (red houses within red circles) being selected, and then all units within those selected groups are included in the sample. - This method is typically used when the population is naturally divided into groups, such as geographical areas or blocks, making it **cost-effective** and practical, especially in large, dispersed populations like an urban slum. *Simple random sampling* - This method would involve **randomly selecting individual houses** from the entire slum without any pre-defined grouping, which is not depicted in the image. - Each house would have an **equal chance of being selected**, and sampling would not be restricted to specific clusters. *Systematic random sampling* - Involves selecting houses at a **fixed interval** (e.g., every 5th house) from a sorted list or along a defined path after a random starting point. - The image does not show a systematic selection process or an underlying order for sampling the houses. *Stratified random sampling* - This method involves **dividing the population into homogeneous subgroups** (strata) based on a characteristic (e.g., age, income level) and then drawing a random sample from each stratum. - While the map shows 'sections', these are not necessarily strata based on a relevant characteristic, and the sampling is not shown to be proportional or disproportional across these sections.
Question 9: Which of the following is a non-probability sampling method?
- A. Simple random sampling
- B. Systematic random sampling
- C. Cluster sampling
- D. Quota sampling (Correct Answer)
Explanation: ***Quota sampling*** - In **quota sampling**, researchers select participants based on specific characteristics (e.g., age, gender, ethnicity) to ensure the sample reflects the population proportions of these characteristics. - This method is **non-probability** because the selection of individuals within each quota is not random, and not every member of the population has an equal chance of being selected. *Simple random sampling* - **Simple random sampling** is a **probability sampling method** where every member of the population has an equal and independent chance of being selected. - This is typically achieved through random number generators or drawing names from a hat. *Systematic random sampling* - **Systematic random sampling** is a **probability sampling method** where sample members are selected at regular intervals from a list of the population. - The starting point is chosen randomly, but subsequent selections follow a predetermined pattern, ensuring a systematic, yet random, selection. *Cluster sampling* - **Cluster sampling** is a **probability sampling method** where the population is divided into naturally occurring groups (clusters), and then a random sample of these clusters is chosen. - Once clusters are selected, all individuals within the chosen clusters, or a random sample of individuals from them, are included in the study.
Question 10: In a village, every fifth house was selected for a study. This is an example of
- A. Simple random sampling
- B. Convenience sampling
- C. Systematic random sampling (Correct Answer)
- D. Stratified random sampling
Explanation: ***Systematic random sampling*** - This method involves selecting subjects from a **ordered sampling frame** at regular intervals, such as every k-th item. - In this scenario, selecting every fifth house represents a fixed interval (k=5), which is characteristic of systematic random sampling. *Simple random sampling* - This method ensures that every member of the population has an **equal chance of being selected**, often through random number generation. - It does not involve a predetermined, fixed interval of selection from an ordered list. *Convenience sampling* - This technique involves selecting subjects who are **easily accessible or readily available**, without any systematic or random process. - It is prone to bias as it does not represent the entire population. *Stratified random sampling* - This method involves dividing the population into **homogeneous subgroups (strata)** and then conducting simple random sampling within each stratum. - The scenario does not describe dividing the village households into distinct subgroups before selection.
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