Biostatistics Practice Questions

Q: Two screening tests in series will increase which of the following?

Both Specificity and Positive predictive value. ### Explanation In screening, the arrangement of tests (Series vs. Parallel) significantly impacts the validity and predictive value of the diagnostic process. **Why Option D is Correct:** When tests are conducted in **Series**, a patient must test positive on the first test AND the second test to be considered "positive." 1. **Specificity Increases:** This "double-check" mechanism filters out false positives. Since it is harder to pass both tests, fewer healthy people are misdiagnosed as diseased, thereby increasing specificity. 2. **Positive Predictive Value (PPV) Increases:** PPV is directly proportional to specificity. By reducing false positives, the probability that a person with a positive result actually has the disease increases. **Why Other Options are Incorrect:** * **Option A & C:** **Sensitivity decreases** in series testing because a person must test positive twice; if they miss either test, they are labeled negative (increasing false negatives). Consequently, **Negative Predictive Value (NPV)** also tends to decrease or remain less optimized compared to parallel testing. * **Option B:** While specificity does increase, it is not the *only* parameter affected. The PPV increases as a mathematical consequence of the improved specificity. **High-Yield Clinical Pearls for NEET-PG:** * **Tests in Parallel:** (e.g., ordering an EKG and Troponin simultaneously) **Increases Sensitivity** and **NPV**. It is used when you don't want to miss a single case (e.g., emergency room). * **Tests in Series:** (e.g., ELISA followed by Western Blot for HIV) **Increases Specificity** and **PPV**. It is used when the treatment is risky or expensive, and you must be certain of the diagnosis. * **Mnemonic:** **S**eries = **S**pecificity (Both start with 'S'). **P**arallel = **S**ensitivity (Think: "Parallel protects against missing cases").

Q: If the first quartile of a dataset is 34, what percentage of observations will be greater than this value?

75%. ### Explanation **Concept of Quartiles** In biostatistics, quartiles are values that divide a dataset—ordered from lowest to highest—into four equal parts, each containing 25% of the observations. * **First Quartile (Q1):** Also known as the 25th percentile. It marks the point below which 25% of the data lies. * **Second Quartile (Q2):** The Median (50th percentile). * **Third Quartile (Q3):** The 75th percentile. **Why Option B is Correct** The question states that the first quartile (Q1) is 34. By definition, Q1 separates the lowest 25% of the data from the upper 75%. Therefore, if 25% of the observations are less than 34, then **75% (100% - 25%)** of the observations must be greater than 34. **Analysis of Incorrect Options** * **Option A (25%):** This represents the percentage of observations *less than* or equal to the first quartile, not greater than it. * **Option C (37%) & Option D (66%):** These values do not correspond to standard quartile divisions (25%, 50%, or 75%) and are mathematically incorrect in this context. **Clinical Pearls & High-Yield Facts for NEET-PG** 1. **Interquartile Range (IQR):** Calculated as $Q3 - Q1$. It represents the middle 50% of the data and is the preferred measure of dispersion for skewed distributions. 2. **Box-and-Whisker Plot:** This graphical representation specifically uses quartiles. The "box" represents the IQR, and the line inside the box represents the Median (Q2). 3. **Relationship with Percentiles:** * $Q1 = 25^{th}$ percentile * $Q2 = 50^{th}$ percentile (Median) * $Q3 = 75^{th}$ percentile 4. **Robustness:** Quartiles and the Median are "resistant" measures, meaning they are not influenced by extreme outliers, unlike the Mean and Standard Deviation.

Q: In a town with a population of 5000, 500 individuals had myopia on January 1, 2011. By December 31, 2011, 90 new cases of myopia were identified. What is the incidence of myopia in the town during 2011?

0.02. ### Explanation **1. Understanding the Correct Answer (B: 0.02)** Incidence measures the number of **new cases** occurring in a **population at risk** during a specific period. The formula is: $$\text{Incidence} = \frac{\text{Number of new cases during a specific period}}{\text{Population at risk during that period}} \times 1000$$ * **New Cases:** 90 * **Population at Risk:** This is the total population minus those who already have the disease (since they are no longer "at risk" of developing it). * Population at risk = $5000 (\text{Total}) - 500 (\text{Existing cases}) = 4500$. * **Calculation:** $90 / 4500 = 0.02$. **2. Analysis of Incorrect Options** * **Option A (0.018):** This is calculated by dividing new cases by the *total* population ($90/5000$). This is a common mistake; you must subtract the prevalent cases from the denominator to find the true population at risk. * **Option C (0.05):** This represents the **Point Prevalence** at the start of the year ($500/5000 = 0.1$) or a miscalculation of the data. * **Option D (18):** This is likely the result of calculating the rate per 1000 ($90/5000 \times 1000$), but it uses the wrong denominator and incorrect decimal placement for the requested value. **3. NEET-PG High-Yield Pearls** * **Incidence vs. Prevalence:** Incidence = New cases (Rate); Prevalence = All cases (Ratio). * **Denominator Rule:** Always exclude individuals who already have the disease or are immune (e.g., vaccinated) from the denominator when calculating incidence. * **Attack Rate:** A type of incidence rate used specifically during epidemics for a limited period (e.g., food poisoning). * **Relationship:** $\text{Prevalence} = \text{Incidence} \times \text{Mean Duration of disease } (P = I \times D)$. This is applicable for stable chronic conditions.

Q: In which of the following study designs does the case act as its own control?

Cross-over study. **Explanation:** In a **Cross-over study**, each participant receives two or more treatments in a sequential manner. The key feature is that after the first intervention and a subsequent "washout period," the participant switches to the alternative treatment. Because the same individual is monitored under both the intervention and the control conditions, the **case acts as its own control**. This design is highly efficient as it eliminates "inter-individual variation" (confounding factors like genetics, age, or lifestyle), requiring a smaller sample size to achieve statistical significance. **Analysis of Incorrect Options:** * **Retrospective study:** Usually refers to a case-control design where researchers look backward in time to find exposures. It compares two different groups of people (cases vs. controls). * **Prospective study:** Typically refers to a cohort study where a group is followed forward in time. It compares exposed individuals to a separate group of unexposed individuals. * **Case-control study:** This design compares a group of people with a disease (cases) to a separate group of people without the disease (controls). The controls are different individuals, not the cases themselves. **Clinical Pearls for NEET-PG:** * **Washout Period:** The time allowed for the first drug to be eliminated from the body to prevent a **"carry-over effect"** into the next phase. * **Suitability:** Cross-over studies are ideal for **chronic, stable conditions** (e.g., asthma, hypertension, migraine) but are **not** suitable for acute illnesses or conditions cured by the first treatment. * **Bias:** The main concern in cross-over trials is the "period effect" or "order effect."

Q: Mammography has 90% sensitivity and 98% specificity for breast carcinoma. What is the probability that a woman with breast carcinoma remains undiagnosed for 2 consecutive years?

1%. ### Explanation **1. Understanding the Correct Answer (1%)** To solve this, we must first identify the **False Negative Rate (FNR)**. * **Sensitivity** is the ability of a test to correctly identify those with the disease. Here, it is 90% (0.9). * The **False Negative Rate** is the probability that a person *with* the disease tests negative. It is calculated as: $1 - \text{Sensitivity}$. * $1 - 0.90 = 0.10$ (or 10%). The question asks for the probability of remaining undiagnosed for **two consecutive years**. Since each year's screening is an independent event, we use the **Multiplication Rule of Probability**: * Year 1 False Negative (0.10) × Year 2 False Negative (0.10) = **0.01 or 1%**. **2. Why Other Options are Incorrect** * **10% (Implicitly considered):** This represents the probability of a false negative in a single year. It fails to account for the second consecutive screening. * **2%:** This is a common distractor often confused with the complement of specificity (False Positive Rate). Specificity (98%) is irrelevant here because the question specifies the woman *has* breast carcinoma. * **0.1%:** This would be the result if the sensitivity were 99% ($0.01 \times 0.01$). **3. Clinical Pearls & High-Yield Facts for NEET-PG** * **Sensitivity (True Positive Rate):** Best for **screening** tests (SNOUT: Sensitivity rules OUT). * **Specificity (True Negative Rate):** Best for **confirmatory** tests (SPIN: Specificity rules IN). * **False Negative Rate (Type II Error/β):** The probability of missing a diagnosis. * **False Positive Rate (Type I Error/α):** Calculated as $1 - \text{Specificity}$. * **Sequential Testing:** When two tests are used in series (like yearly mammograms), the overall sensitivity decreases, but the overall specificity increases. However, the probability of a "miss" (False Negative) across multiple tests is the product of individual false negative rates.

Q: Twenty-five children are chosen randomly from a school playground. Their heights are measured in 2 consecutive months. What statistical test could be used to test the hypothesis that their heights are not different in consecutive months?

Paired t-test. ### Explanation **Why Paired t-test is the Correct Answer:** The core concept here is the **comparison of means in a "before-and-after" scenario** involving the same group of individuals. In this question, the same 25 children are measured twice (Month 1 and Month 2). Since the two sets of data are dependent (linked to the same person), we use the **Paired t-test**. This test evaluates whether the mean difference between these two related observations is significantly different from zero. **Analysis of Incorrect Options:** * **A. Unpaired t-test (Independent t-test):** This is used to compare the means of two **independent** groups (e.g., comparing heights of 25 children from School A with 25 different children from School B). * **C. Z-test:** While also used to compare means, a Z-test requires a **large sample size (n > 30)** and a known population variance. Here, the sample size is small (n = 25). * **D. Regression:** This is used to determine the **strength and direction of a relationship** between a dependent and independent variable (e.g., how much height increases for every year of age), rather than testing the difference between two sets of measurements. **High-Yield Clinical Pearls for NEET-PG:** * **Paired data** occurs in: Before-after studies, cross-over trials, and case-control studies with 1:1 matching. * **Parametric vs. Non-parametric:** If the data were not normally distributed, the non-parametric alternative to the Paired t-test would be the **Wilcoxon Signed-Rank Test**. * **Sample Size Rule:** Use **t-test** for n 30. * **ANOVA:** Use this when comparing means of **more than two** independent groups.

Q: For a group of 250 subjects, what value represents the 40th percentile?

100. **Explanation:** **1. Why the Correct Answer is Right:** In biostatistics, a **percentile** is a measure used to indicate the value below which a given percentage of observations in a group of observations falls. To calculate the position of a specific percentile in a dataset, the formula used is: * **Rank (n) = (P / 100) × N** * *P* = Percentile (40) * *N* = Total number of subjects (250) Applying the formula: $(40 / 100) \times 250 = 0.4 \times 250 = \mathbf{100}$. Therefore, the 100th value in the ordered dataset represents the 40th percentile. **2. Why Incorrect Options are Wrong:** * **Option A (7):** This is a random low number and does not correspond to any standard statistical calculation for this dataset. * **Option B (40):** This is a common distractor where students confuse the *percentile rank* (40th) with the *absolute value* (100). 40 is the percentage, not the count of subjects. * **Option D (140):** This value is mathematically incorrect. It might be reached if a student incorrectly adds the percentile to the total or miscalculates the percentage. **3. NEET-PG High-Yield Clinical Pearls:** * **Median:** The 50th percentile is always the Median. In this dataset, the median would be the 125th value. * **Quartiles:** The 25th percentile is the 1st Quartile (Q1), and the 75th percentile is the 3rd Quartile (Q3). * **Interquartile Range (IQR):** Calculated as Q3 – Q1; it contains the middle 50% of the data and is used to describe skewed distributions. * **Growth Charts:** In clinical practice, percentiles are most commonly used in pediatric growth charts (e.g., a child at the 95th percentile for weight is heavier than 95% of children their age).

Question 1

Two screening tests in series will increase which of the following?

Accepted Answer

Both Specificity and Positive predictive value

Answer

Sensitivity alone

Answer

Specificity alone

Answer

Both Sensitivity and Negative predictive value

Question 2

If the first quartile of a dataset is 34, what percentage of observations will be greater than this value?

Accepted Answer

75%

Answer

25%

Answer

37%

Answer

66%

Question 3

In a town with a population of 5000, 500 individuals had myopia on January 1, 2011. By December 31, 2011, 90 new cases of myopia were identified. What is the incidence of myopia in the town during 2011?

Accepted Answer

0.02

Answer

0.018

Answer

0.05

Answer

18

Question 4

In which of the following study designs does the case act as its own control?

Accepted Answer

Cross-over study

Answer

Retrospective study

Answer

Prospective study

Answer

Case-control study

Question 5

In a given population, approximately 10% of all deaths in the age group 0 to 14 years were due to accidents and injuries. In the same population, 20% of all deaths in the age group 15 to 35 years were due to accidents and injuries. How many times is the risk of dying due to accidents and injuries among 15 to 35 years as compared to the 0-14 years age group?

Accepted Answer

Cannot be concluded from the data

Answer

2

Answer

0.5

Answer

1

Question 6

Mammography has 90% sensitivity and 98% specificity for breast carcinoma. What is the probability that a woman with breast carcinoma remains undiagnosed for 2 consecutive years?

Accepted Answer

1%

Answer

2%

Answer

2%

Question 7

Twenty-five children are chosen randomly from a school playground. Their heights are measured in 2 consecutive months. What statistical test could be used to test the hypothesis that their heights are not different in consecutive months?

Accepted Answer

Paired t-test

Answer

Unpaired t-test

Answer

Z-test

Answer

Regression

Question 8

For a group of 250 subjects, what value represents the 40th percentile?

Accepted Answer

100

Answer

7

Answer

40

Answer

140

Question 9

A screening test for colon cancer was applied to 1000 individuals. The test was positive in 320 and negative in 680. Of those with a positive test, 60 actually had the disease. Of those with a negative test, 20 actually had the disease. Calculate the positive predictive value of the test.

Accepted Answer

81%

Answer

12%

Answer

75%

Answer

28%

Question 10

If the American Heart Association lowered the cut-off threshold for hypertension, what would be the effect on the properties of blood pressure assessment as a screening test?

Accepted Answer

The negative predictive value will rise

Answer

The false negative rate will rise

Answer

The positive predictive value will rise

Answer

The sensitivity will fall

Biostatistics — MCQs

Biostatistics — MCQs

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