Biostatistics Practice Questions

Q: In a case-control study on hypertension and stroke, which measure is used to compare the risk between cases and controls?

Odds ratio. ***Odds ratio*** - In a **case-control study**, we start by identifying individuals with the outcome (cases) and those without (controls) and then look back to assess their exposure status. - The **odds ratio (OR)** quantifies the odds of exposure among cases relative to the odds of exposure among controls, thereby estimating the strength of association between exposure and outcome. *Relative risk* - **Relative risk (RR)** is used in **cohort studies** and **randomized controlled trials** to compare the risk of an outcome in an exposed group versus an unexposed group. - It directly measures how many times more likely an exposed group is to develop an outcome compared to an unexposed group. *Absolute risk reduction* - **Absolute risk reduction (ARR)** is a measure of the difference in risk between an intervention group and a control group, typically used in **clinical trials**. - It indicates the **absolute difference in the proportion of people** who experience an event across two groups, reflecting the direct benefit of an intervention. *Incidence rate* - The **incidence rate** measures the number of new cases of a disease or outcome that develop in a population at risk over a specified period. - It is used to describe the **frequency of disease occurrence** in a population, not to compare risk between cases and controls.

Q: A study evaluates the impact of a new diabetes management program on patient outcomes. Which method is the best to analyze the effectiveness of the program?

Randomized controlled trial. ***Randomized controlled trial*** - A **Randomized Controlled Trial (RCT)** is the **gold standard** for evaluating interventions because it minimizes bias by randomly assigning participants to either an intervention group or a control group. - This design allows for a direct comparison of outcomes, providing the strongest evidence of a program's **effectiveness** by controlling for confounding variables and ensuring that observed effects are likely due to the intervention. *Pre- and post-intervention comparison* - This method compares outcomes before and after an intervention in the same group of participants, but it lacks a **control group**. - Without a control group, it's difficult to attribute observed changes solely to the intervention, as other **confounding factors** or natural progression of the disease could also influence the results. *Cross-sectional survey* - A **cross-sectional survey** collects data at a single point in time, providing a snapshot of the prevalence of certain characteristics or outcomes. - This method is useful for describing populations but **cannot establish causality** or measure changes over time in response to an intervention. *Cohort study* - A **cohort study** follows a group of individuals over time to observe the development of outcomes, often comparing those exposed to a risk factor with those unexposed. - While useful for studying **risk factors** and disease incidence, it typically does not involve a controlled intervention and is more prone to **confounding biases** than an RCT when assessing program effectiveness.

Q: A health researcher wants to compare the effectiveness of two different antihypertensive drugs. Which statistical test should be used to determine if there is a significant difference in blood pressure reduction between the two groups?

t-test. ***t-test*** - The **t-test** is appropriate for comparing the means of **two independent groups** to determine if a significant difference exists. In this scenario, we are comparing the mean blood pressure reduction between two drug groups. - Specifically, an **independent samples t-test** would be used as the two drug groups are distinct and unrelated. *Chi-square test* - The **chi-square test** is used to compare **categorical data** or frequencies, not continuous variables like blood pressure reduction. - It assesses whether there is a significant association between two categorical variables. *ANOVA* - **ANOVA (Analysis of Variance)** is used to compare the means of **three or more independent groups**. - While it *could* be used for two groups (and would yield the same p-value as a t-test), the **t-test** is the more direct and appropriate choice for a two-group comparison. *Correlation analysis* - **Correlation analysis** measures the strength and direction of a **linear relationship between two continuous variables**. - It does not test for significant differences between group means but rather how two variables move together.

Q: A researcher is calculating the standard error of the mean for a sample of 100 patients with a standard deviation of 10. What is the standard error of the mean?

1.0. ***Correct Answer: 1.0*** - The **standard error of the mean (SEM)** is calculated by dividing the **sample standard deviation** by the square root of the **sample size**. - Formula: SEM = SD / √n - In this case: SEM = 10 / √100 = 10 / 10 = **1.0** - SEM quantifies the **precision of the sample mean** as an estimate of the population mean. *Incorrect: 0.1* - This result would be obtained if the standard deviation was divided by 100 instead of the square root of 100 (i.e., 10/100 = 0.1). - Alternatively, this would be correct if SD = 1 and n = 100 (1/√100 = 0.1). - Represents a miscalculation where **√n was confused with n**. *Incorrect: 10.0* - This value is simply the **standard deviation** itself, not the standard error of the mean. - Common error: **forgetting to divide by √n** in the SEM formula. - Standard deviation measures the spread of individual data points, whereas SEM measures the **variability of sample means**. *Incorrect: 5.0* - This value would result if the standard deviation was divided by √4 instead of √100 (i.e., 10/2 = 5.0). - Represents a miscalculation with the **wrong sample size** used in the denominator. - Does not align with the given values (SD = 10, n = 100).

Q: In a case-control study investigating the link between smoking and lung cancer, which measure of association is the most appropriate?

Odds ratio. ***Odds ratio*** - The **odds ratio** is the most appropriate measure of association for **case-control studies** because these studies select participants based on disease status, making direct calculation of incidence or relative risk impossible. - It approximates the **relative risk** when the disease is rare, providing a valid estimate of the association between the exposure (smoking) and the outcome (lung cancer). *Relative risk* - **Relative risk** is calculated in **cohort studies** where participants are followed over time to observe the incidence of disease in exposed versus unexposed groups. - It cannot be directly calculated in a **case-control study** because the study design ascertains cases and controls based on outcome, not exposure status. *Attributable risk* - **Attributable risk**, also known as risk difference, measures the absolute excess risk of disease in the exposed group compared to the unexposed group. - Like relative risk, it is primarily used in **cohort studies** to determine the benefit of removing an exposure, and it requires incidence data. *Incidence rate* - **Incidence rate** measures the frequency with which new cases of disease occur in a population at risk over a specified period. - It is a measure reported in **cohort studies** or surveillance studies, not typically in case-control studies, which are designed to compare exposures between cases and controls.

Q: From a population of 100,000, a sample of 100 women's hemoglobin is measured with a standard deviation of 2 gm%. What is the standard error of the mean?

0.2 gm%. ***0.2 gm%*** - The **standard error of the mean (SEM)** is calculated by dividing the population **standard deviation (SD)** by the square root of the **sample size (n)**. - Given SD = 2 gm% and n = 100, the SEM = 2 / √100 = 2 / 10 = **0.2 gm%.** *1 gm%* - This value would be obtained if the standard deviation was 10 gm% or if the sample size was 4 (2/√4 = 1), which is incorrect. - It does not reflect the given standard deviation or sample size in the standard error formula. *0.1 gm%* - This value would be correct if the standard deviation was 1 gm% (1/√100 = 0.1 gm%). - It does not align with the provided standard deviation of 2 gm%. *2 gm%* - This value represents the original **standard deviation** itself, not the standard error of the mean. - The standard error should be smaller than the standard deviation when the sample size is greater than 1.

Q: During a mass screening program for diabetes, a new test with a sensitivity of 85% and specificity of 90% is used. If the test is applied to a population with a low prevalence of diabetes, what is the most likely outcome?

Increased false positive results due to low prevalence. ***Increased false positive results due to low prevalence*** - In a population with **low disease prevalence**, even a test with high specificity will yield a significant number of **false positives** because there are many healthy individuals who will test positive. - While sensitivity and specificity are intrinsic to the test, the **positive predictive value (PPV)**, which reflects the likelihood of actually having the disease when testing positive, decreases dramatically with lower disease prevalence. *Increased true positive results due to high sensitivity* - While **high sensitivity** does mean that a large proportion of truly diseased individuals will be correctly identified as positive, the absolute number of **true positives** will be low if the disease itself is rare in the population. - The number of true positives is also directly limited by the **prevalence** of the disease. *Increased false negative results due to low prevalence* - **False negative results** are primarily influenced by the test's **sensitivity**, not directly by prevalence. A test with 85% sensitivity will miss 15% of true cases, regardless of how common or rare the disease is. - Low prevalence means there are fewer actual cases to begin with, so the absolute number of false negatives might be low, but the *proportion* of missed cases among true positives remains related to sensitivity. *Equal false positive and false negative results* - It is highly unlikely for **false positive** and **false negative** rates to be equal, as they are determined by different test characteristics (**specificity** and **sensitivity**, respectively) which are independent. - The impact of prevalence primarily skews the balance between false positives and true positives, and false negatives and true negatives.

Q: A researcher is conducting a study on the impact of air pollution on respiratory health. Which of the following study designs is best suited for this type of research?

Cohort study. ***Cohort study*** - A **cohort study** tracks a group of individuals over time, comparing those exposed to air pollution with an unexposed group to observe the development of respiratory outcomes. - This design allows for the calculation of **incidence rates** and establishes a temporal relationship between exposure and disease, which is crucial for studying environmental health impacts. *Case-control study* - A **case-control study** starts with individuals who already have the respiratory disease (cases) and compares their past exposure to air pollution with that of individuals without the disease (controls). - While useful for rare diseases, it is more prone to **recall bias** regarding past exposures and cannot directly measure incidence. *Cross-sectional study* - A **cross-sectional study** assesses exposure and outcome simultaneously at a single point in time. - It can determine prevalence but cannot establish a **temporal relationship** between air pollution exposure and the development of respiratory health issues. *Randomized controlled trial* - A **randomized controlled trial (RCT)** involves randomly assigning participants to an intervention group (e.g., reduced air pollution exposure) or a control group. - While ideal for establishing causality, it is **unethical and impractical** to intentionally expose people to air pollution to study its harmful effects.

Question 1

In a case-control study on hypertension and stroke, which measure is used to compare the risk between cases and controls?

Accepted Answer

Odds ratio

Answer

Relative risk

Answer

Absolute risk reduction

Answer

Incidence rate

Question 2

In a randomized controlled trial, the relative risk reduction (RRR) for a new treatment compared to the standard treatment is calculated to be 25%. How should this result be interpreted?

Accepted Answer

The new treatment reduces the risk of the outcome by 25% compared to the standard treatment.

Answer

25% of patients in the treatment group did not experience the outcome.

Answer

The risk of the outcome is 25% of what it was in the standard treatment group.

Answer

The new treatment is 25% less effective than the standard treatment.

Question 3

A public health researcher is comparing the effectiveness of two vaccines using a cohort study. After calculating the relative risk, the researcher finds an RR of 0.5 for Vaccine A compared to Vaccine B. What does this result indicate about Vaccine A?

Accepted Answer

Vaccine A reduces the risk of disease by 50% compared to Vaccine B.

Answer

Vaccine A increases the risk of disease by 50% compared to Vaccine B.

Answer

Vaccine A has no effect on disease risk compared to Vaccine B.

Answer

Vaccine A and Vaccine B are equally effective.

Question 4

A study evaluates the impact of a new diabetes management program on patient outcomes. Which method is the best to analyze the effectiveness of the program?

Accepted Answer

Randomized controlled trial

Answer

Pre- and post-intervention comparison

Answer

Cross-sectional survey

Answer

Cohort study

Question 5

A health researcher wants to compare the effectiveness of two different antihypertensive drugs. Which statistical test should be used to determine if there is a significant difference in blood pressure reduction between the two groups?

Accepted Answer

t-test

Answer

Chi-square test

Answer

ANOVA

Answer

Correlation analysis

Question 6

A researcher is calculating the standard error of the mean for a sample of 100 patients with a standard deviation of 10. What is the standard error of the mean?

Accepted Answer

1.0

Answer

0.1

Answer

10.0

Answer

5.0

Question 7

In a case-control study investigating the link between smoking and lung cancer, which measure of association is the most appropriate?

Accepted Answer

Odds ratio

Answer

Relative risk

Answer

Attributable risk

Answer

Incidence rate

Question 8

From a population of 100,000, a sample of 100 women's hemoglobin is measured with a standard deviation of 2 gm%. What is the standard error of the mean?

Accepted Answer

0.2 gm%

Answer

2 gm%

Answer

1 gm%

Answer

0.1 gm%

Question 9

During a mass screening program for diabetes, a new test with a sensitivity of 85% and specificity of 90% is used. If the test is applied to a population with a low prevalence of diabetes, what is the most likely outcome?

Accepted Answer

Increased false positive results due to low prevalence

Answer

Increased true positive results due to high sensitivity

Answer

Increased false negative results due to low prevalence

Answer

Equal false positive and false negative results

Question 10

A researcher is conducting a study on the impact of air pollution on respiratory health. Which of the following study designs is best suited for this type of research?

Accepted Answer

Cohort study

Answer

Case-control study

Answer

Cross-sectional study

Answer

Randomized controlled trial

Biostatistics — MCQs

Biostatistics — MCQs

On this page

Practice by Chapter

Want unlimited practice?