Biostatistics Practice Questions

Q: A screening program for breast cancer uses mammography with 85% sensitivity and 90% specificity. In a population with 2% breast cancer prevalence, what percentage of positive test results will be false positives?

83%. ***83%*** - Approximately 83% of positive test results will be **false positives**. This is calculated by finding the overall proportion of positive tests (true positives + false positives) and then determining the percentage of false positives within that total. - Given a 2% prevalence, 0.017 true positives (0.02 × 0.85) and 0.098 false positives (0.98 × 0.10) occur. The total positive tests are 0.017 + 0.098 = 0.115. The false positive percentage is (0.098 / 0.115) × 100% = **85.2%**. This value is closest to 83%. Note: Slight numerical differences can arise from rounding. *10%* - This value likely reflects the **false positive rate** (1 - specificity = 1 - 0.90 = 0.10 or 10%) but not the percentage of positive test results that are false positives. - The false positive rate (1-specificity) refers to the proportion of healthy individuals who test positive, not the proportion of all positive tests that are false. *15%* - This value is related to the **false negative rate** (1 - sensitivity = 1 - 0.85 = 0.15 or 15%), which is not what the question is asking. - The false negative rate indicates the proportion of individuals with the disease who test negative. *98%* - This number represents the **prevalence of healthy individuals** (1 - prevalence of disease = 1 - 0.02 = 0.98 or 98%), which is used in the calculation but is not the answer itself. - It doesn't directly answer the question about the proportion of false positives among all positive tests.

Q: A pharmaceutical company wants to test a new medication. They recruit 1000 healthy volunteers and randomly assign 500 to receive the medication and 500 to receive a placebo. Neither participants nor researchers know who receives which treatment. What type of study design is this?

Double-blind randomized controlled trial. ***Double-blind randomized controlled trial*** - This design involves **random assignment** to treatment or placebo groups, a hallmark of an RCT, and ensures that neither participants nor researchers know who received which treatment (**double-blind**). - This methodology **minimizes bias** and is considered the **gold standard** for establishing causality and evaluating the efficacy of new interventions. *Case-control study* - This study design **compares individuals with a disease/outcome (cases)** to individuals without it (controls) to look for past exposures. - It works **retrospectively**, looking back in time to identify exposures, which is different from the prospective intervention described. *Cohort study* - A cohort study **follows a group of individuals (a cohort)** over time to observe the development of disease or outcomes. - While prospective, it is primarily **observational** and does not involve the active intervention and random assignment of a new medication. *Cross-sectional study* - This type of study **measures exposure and outcome simultaneously** at a single point in time, providing a "snapshot" of a population. - It cannot establish **causality** or the effect of an intervention over time due to its single-point assessment.

Q: A new screening test for disease X has a sensitivity of 90% and specificity of 80%. In a population where the prevalence of disease X is 5%, what is the positive predictive value of this test?

19.1%. ***19.1%*** - The **positive predictive value (PPV)** is calculated using **Bayes' theorem**: `PPV = (Sensitivity × Prevalence) / [(Sensitivity × Prevalence) + ((1 - Specificity) × (1 - Prevalence))]`. - Plugging in the values: `PPV = (0.90 × 0.05) / [(0.90 × 0.05) + ((1 - 0.80) × (1 - 0.05))] = 0.045 / [0.045 + (0.20 × 0.95)] = 0.045 / (0.045 + 0.19) = 0.045 / 0.235 ≈ 0.1914`, or **19.1%**. *90%* - This value represents the **sensitivity** of the test, not the positive predictive value. - Sensitivity is the proportion of true positives among all individuals with the disease, not the probability of having the disease given a positive test result. *45%* - This incorrect value might arise from simply multiplying sensitivity and prevalence (0.90 × 0.05 = 0.045 = 4.5%), then mistakenly multiplying by 10. - It does not correspond to any standard epidemiological metric and results from miscalculation of PPV. *72%* - This incorrect value does not align with the standard PPV formula using the provided sensitivity, specificity, and prevalence. - This may result from miscalculating the denominator or incorrectly applying the formula, such as ignoring the false positive component.

Q: A researcher wants to study the relationship between smoking and lung cancer. She identifies 500 patients with lung cancer and 500 controls without lung cancer, then investigates their smoking history. What type of study design is this?

Case-control study. ***Case-control study*** - This study design **compares individuals with a disease (cases) to individuals without the disease (controls)** and retrospectively examines their exposure to risk factors. - The researcher identified patients with lung cancer (cases) and those without (controls) and then looked back at their smoking history (exposure). *Cross-sectional study* - A **cross-sectional study** assesses both exposure and outcome simultaneously at a single point in time. - It provides a snapshot of the prevalence of an outcome and associated factors but cannot establish causality. *Cohort study* - A **cohort study** follows a group of individuals (cohort) over time to see who develops the disease based on their initial exposure status. - It starts with exposed and unexposed groups and tracks them forward to observe disease incidence. *Randomized controlled trial* - A **randomized controlled trial (RCT)** involves random assignment of participants to different intervention groups, including a control group. - RCTs are used to test the effectiveness of interventions and are prospective in nature, not retrospective.

Q: Interpret the following graph.

Normal, positively skewed, negatively skewed, normal with outliers. ### ***Normal, positively skewed, negatively skewed, normal with outliers*** - Boxplot 1 shows a relatively symmetric distribution with the median line close to the center of the box and whiskers of similar length, indicating a **normal distribution**. - Boxplot 2 has its median shifted towards the lower quartile and a longer whisker/tail on the right side, characteristic of a **positively skewed (right-skewed) distribution**. - Boxplot 3 has its median shifted towards the upper quartile and a longer whisker/tail on the left side, indicating a **negatively skewed (left-skewed) distribution**. - Boxplot 4 shows a relatively symmetric distribution, but with individual data points (represented by dots) extending beyond the whiskers, which are considered **outliers** in an otherwise **normal distribution**. ### *Normal, negatively skewed, positively skewed, skewed with outliers* - This option incorrectly identifies the skewness for plots 2 and 3. Plot 2 is positively skewed, not negatively, and plot 3 is negatively skewed, not positively. - While plot 4 does have outliers, referring to it simply as "skewed with outliers" is less precise when its central distribution appears normal. ### *Skewed with outliers, positively skewed, negatively skewed, normal* - This option incorrectly identifies plot 1 as "skewed with outliers" when it appears normal. - It also incorrectly reverses the descriptions for plot 2 (positively skewed) and plot 4 (normal with outliers). ### *Normal, negatively skewed, positively skewed, normal with outliers* - This option incorrectly identifies the skewness for plot 2, labeling it as negatively skewed instead of positively skewed. - It also incorrectly labels plot 3 as positively skewed, when it is negatively skewed.

Q: A study is performed to assess the intelligence quotient and the crime rate in a neighborhood. Students at a local high school are given an assessment and their criminal and disciplinary records are reviewed. One of the subjects scores 2 standard deviations over the mean. What percent of students did he score higher than?

97.5%. ***97.5%*** - This question relates to the **normal distribution (bell curve) and the empirical rule (68-95-99.7 rule)** [1]. - A score 2 standard deviations above the mean means that 95% of the data falls within +/- 2 standard deviations of the mean [2]. This leaves 5% outside of this range (2.5% on each tail). Therefore, the student scored higher than 95% + 2.5% = **97.5%** of students. *95%* - This percentage represents the data that falls within **2 standard deviations of the mean (both sides)**, not the percentage a score 2 standard deviations above the mean is higher than [1]. - It would be correct if the question asked for the percentage of students whose scores fall within two standard deviations of the mean. *68%* - This percentage represents the data that falls within **1 standard deviation of the mean** according to the empirical rule [1]. - A score 2 standard deviations above the mean is significantly higher than this range. *99.7%* - This percentage represents the data that falls within **3 standard deviations of the mean (both sides)**, according to the empirical rule [2]. - This would mean the student scored 3 standard deviations above the mean, which is not stated in the question.

Question 1

A cohort study follows 10,000 healthcare workers over 10 years to assess the relationship between shift work and cardiovascular disease. What is the main advantage of this study design?

Accepted Answer

It can establish temporal relationships and calculate incidence

Answer

It requires fewer participants than other designs

Answer

It can establish causation definitively

Answer

It is less expensive than other study designs

Question 2

A screening program for breast cancer uses mammography with 85% sensitivity and 90% specificity. In a population with 2% breast cancer prevalence, what percentage of positive test results will be false positives?

Accepted Answer

83%

Answer

10%

Answer

15%

Answer

98%

Question 3

A research study found a statistically significant result with p = 0.03. The confidence interval for the effect size is 0.5 to 2.1. How should this result be interpreted?

Accepted Answer

The result is statistically significant but may not be clinically meaningful

Answer

The p-value is too high to draw any conclusions

Answer

The result is both statistically and clinically significant

Answer

The result is neither statistically nor clinically significant

Question 4

A pharmaceutical company wants to test a new medication. They recruit 1000 healthy volunteers and randomly assign 500 to receive the medication and 500 to receive a placebo. Neither participants nor researchers know who receives which treatment. What type of study design is this?

Accepted Answer

Double-blind randomized controlled trial

Answer

Case-control study

Answer

Cohort study

Answer

Cross-sectional study

Question 5

A new screening test for disease X has a sensitivity of 90% and specificity of 80%. In a population where the prevalence of disease X is 5%, what is the positive predictive value of this test?

Accepted Answer

19.1%

Answer

90%

Answer

45%

Answer

72%

Question 6

A researcher wants to study the relationship between smoking and lung cancer. She identifies 500 patients with lung cancer and 500 controls without lung cancer, then investigates their smoking history. What type of study design is this?

Accepted Answer

Case-control study

Answer

Cross-sectional study

Answer

Cohort study

Answer

Randomized controlled trial

Question 7

A multivariate analysis was conducted to examine the relationship between risk of developing blindness and age. The results are shown in the table below. Which of the following is true?

Accepted Answer

>80 y age group has the strongest association with blindness risk

Answer

60-69 y age group shows statistically significant association with blindness

Answer

<50 y age group serves as the reference category

Answer

50-59 y age group has the highest odds ratio for blindness risk

Question 8

A graph shows four different distribution curves labeled A, B, C, and D. Identify the correct sequence of distribution types shown in the graph.

Accepted Answer

Normal, positively skewed, negatively skewed, normal with outliers

Answer

Skewed with outliers, positively skewed, negatively skewed, normal

Answer

Normal, negatively skewed, positively skewed, skewed with outliers

Answer

Normal, negatively skewed, positively skewed, normal with outliers

Question 9

Interpret the following graph.

Accepted Answer

Normal, positively skewed, negatively skewed, normal with outliers

Answer

Normal, negatively skewed, positively skewed, skewed with outliers

Answer

Skewed with outliers, positively skewed, negatively skewed, normal

Answer

Normal, negatively skewed, positively skewed, normal with outliers

Question 10

A study is performed to assess the intelligence quotient and the crime rate in a neighborhood. Students at a local high school are given an assessment and their criminal and disciplinary records are reviewed. One of the subjects scores 2 standard deviations over the mean. What percent of students did he score higher than?

Accepted Answer

97.5%

Answer

95%

Answer

68%

Answer

99.7%

Biostatistics — MCQs

Biostatistics — MCQs

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