Crossover design MCQs With Answer

Introduction:

This blog presents a focused set of multiple-choice questions on crossover study designs, tailored for M.Pharm students studying Research Methodology & Biostatistics. Crossover trials are widely used in pharmacology and bioequivalence studies because each participant receives multiple treatments, allowing within-subject comparisons and greater statistical efficiency. The questions below cover design types (2×2, Latin square, Williams), washout and carryover effects, appropriate statistical models (Grizzle, mixed-effects ANOVA), sample size and analysis strategies, and practical issues such as dropout handling and bioequivalence criteria. Answers are provided to aid self-assessment and to deepen understanding of methodological choices critical for clinical pharmacology research.

Q1. In a standard 2×2 crossover design (AB/BA), what is the primary advantage compared to a parallel-group design?

• Each subject receives only one treatment, reducing complexity
• It eliminates all period and sequence effects
• Within-subject comparison reduces variability and required sample size
• Treatment carryover is never a concern

Correct Answer: Within-subject comparison reduces variability and required sample size

Q2. Which component is explicitly modeled in the classic Grizzle ANOVA for a 2×2 crossover?

• Carryover, period, treatment and subject-within-sequence effects
• Only treatment and period effects, ignoring carryover
• Random slopes for treatment over time
• Time-varying covariates as fixed effects

Correct Answer: Carryover, period, treatment and subject-within-sequence effects

Q3. What is the usual recommended approach if a significant carryover effect is detected in a 2×2 crossover?

• Ignore it and proceed with pooled analysis
• Analyze only first-period data as a parallel-group comparison
• Combine periods and adjust by increasing sample size
• Switch to nonparametric tests for both periods

Correct Answer: Analyze only first-period data as a parallel-group comparison

Q4. In bioequivalence studies comparing AUC and Cmax, why are pharmacokinetic measures often log-transformed before analysis?

• Log transformation makes the data binary
• It stabilizes variance and makes ratios symmetric for confidence intervals
• Log transform eliminates carryover effects
• It always produces normally distributed data regardless of original distribution

Correct Answer: It stabilizes variance and makes ratios symmetric for confidence intervals

Q5. Which design is specifically used to control first-order carryover across multiple treatments with minimal subjects?

• Parallel-group randomized design
• Latin square or Williams design
• Factorial crossover design
• Open-label sequential design

Correct Answer: Latin square or Williams design

Q6. When calculating sample size for a 2×2 crossover aimed at demonstrating bioequivalence, which parameter is most critical?

• Between-subject variance only
• Within-subject variance of the log-transformed PK measure
• The expected dropout rate only
• Number of sequences regardless of variance estimates

Correct Answer: Within-subject variance of the log-transformed PK measure

Q7. Which assumption underlies the increased efficiency of crossover designs?

• Treatment effects are identical across all subjects and times
• Within-subject correlation is negligible
• Within-subject variability is smaller than between-subject variability
• No period effects exist

Correct Answer: Within-subject variability is smaller than between-subject variability

Q8. In a 2×2 crossover, what does a sequence effect refer to?

• An interaction between subject demographics and treatment
• Difference attributable to the order in which treatments are given
• Random measurement error within a period
• Technical drift in laboratory assays over time

Correct Answer: Difference attributable to the order in which treatments are given

Q9. Which analytic approach is preferred for modern crossover analysis when missing data and unequal variances are possible?

• Paired t-test on change scores only
• Mixed-effects model with fixed effects for sequence, period and treatment and random subject effects
• Nonparametric Wilcoxon signed-rank test always
• Simple ANOVA ignoring subject-level random effects

Correct Answer: Mixed-effects model with fixed effects for sequence, period and treatment and random subject effects

Q10. How is washout period length primarily determined in crossover pharmacokinetic studies?

• By regulatory guidance irrespective of drug pharmacology
• Using a fixed 24-hour rule for all drugs
• Based on drug half-life, typically several half-lives to minimize carryover
• By the longest expected treatment period in the study

Correct Answer: Based on drug half-life, typically several half-lives to minimize carryover

Q11. What is the principal disadvantage of crossover designs?

• They always require larger sample sizes than parallel trials
• Risk of carryover and longer study duration per subject
• They cannot control within-subject variability
• They are unsuitable for chronic stable conditions

Correct Answer: Risk of carryover and longer study duration per subject

Q12. In a Williams design for four treatments, the primary goal is to:

• Maximize number of periods while ignoring balance
• Balance first-order carryover and sequence effects across treatments
• Ensure each subject receives only one treatment
• Assess dose-response within each subject

Correct Answer: Balance first-order carryover and sequence effects across treatments

Q13. Which statement about testing for carryover in crossover trials is correct?

• Significant carryover testing is mandatory and always reliable
• Testing for carryover can be underpowered and is controversial; prevention is preferable
• If carryover test is non-significant, no washout is needed
• Carryover tests remove the need for randomization

Correct Answer: Testing for carryover can be underpowered and is controversial; prevention is preferable

Q14. For bioequivalence, the common acceptance criterion for the 90% confidence interval of the geometric mean ratio is:

• 0.5 to 2.0
• 0.8 to 1.25
• 0.9 to 1.1
• 0.7 to 1.3

Correct Answer: 0.8 to 1.25

Q15. Which effect is tested by including period as a fixed effect in the crossover ANOVA?

• Carryover from previous treatments
• Systematic differences between study periods (e.g., time trends)
• Within-subject random variability
• Subject-by-treatment interaction

Correct Answer: Systematic differences between study periods (e.g., time trends)

Q16. Incomplete or two-stage crossover designs are employed primarily when:

• All subjects can tolerate all treatments without dropout
• There are too many treatments to administer to every subject in a feasible timeframe
• One-period designs are always preferred
• Carryover effects are desired to be maximized

Correct Answer: There are too many treatments to administer to every subject in a feasible timeframe

Q17. What does intra-subject correlation (or within-subject correlation) in crossover trials indicate?

• Correlation between measurements across different subjects
• Degree to which repeated measures on the same subject are related
• Correlation between randomization sequence and outcome
• Association between period number and dropout rate

Correct Answer: Degree to which repeated measures on the same subject are related

Q18. If a two-treatment crossover shows a significant treatment-by-period interaction, the appropriate interpretation is:

• No treatment effect exists
• Treatment effects vary by period, suggesting potential carryover or time-dependent effects
• The study is automatically bioequivalent
• Sequence assignment was successful and no adjustment is needed

Correct Answer: Treatment effects vary by period, suggesting potential carryover or time-dependent effects

Q19. When handling missing data in crossover trials, which strategy is generally recommended?

• Exclude all subjects with any missing data from analysis
• Use modern mixed-model methods that can handle missing-at-random data without biased complete-case removal
• Impute missing data deterministically using the grand mean only
• Replace missing values with zeros to maintain sample size

Correct Answer: Use modern mixed-model methods that can handle missing-at-random data without biased complete-case removal

Q20. Which of the following best describes an advantage of Latin square crossover designs?

• They require no randomization
• They can control for two blocking factors (period and sequence) while balancing treatments
• They are suitable only for two treatments
• They eliminate within-subject variability completely

Correct Answer: They can control for two blocking factors (period and sequence) while balancing treatments

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