- Matching.
- Stratification.
- Randomization.
- Blinding.
No category found.
- Descriptive statistics.
- Probability.
- Inferential statistics.
- Data visualization.
- Independent samples t-test.
- Paired t-test.
- Chi-square test.
- One-way ANOVA.
- Small sample size makes the finding more reliable.
- Small sample size can lead to unstable estimates and findings that may not replicate in larger studies.
- The p-value is always accurate regardless of sample size.
- The study had high power.
- Histogram.
- Scatter plot.
- Kaplan-Meier curve.
- Box plot.
- Sample.
- Statistic.
- Population.
- Parameter.
- The null hypothesis assumes the new drug is inferior by a pre-specified margin.
- The null hypothesis assumes the new drug is superior.
- The significance level is ignored.
- Non-inferiority trials do not use hypothesis testing.
- Simple linear regression.
- Multiple linear regression.
- Multiple logistic regression.
- Poisson regression.
- Bar chart.
- Pie chart.
- Histogram.
- Scatter plot.
- To immediately stop the trial because of small benefits.
- To weigh the statistical significance against the clinical relevance and potential harms, recognizing that a statistically significant effect may not be clinically meaningful.
- To continue the trial regardless of clinical significance.
- To only consider the p-value.
- Alternative hypothesis.
- Research hypothesis.
- Null hypothesis.
- Statistical hypothesis.
- Nominal.
- Ordinal.
- Discrete.
- Continuous.
- The null hypothesis of no effect is likely true.
- The null hypothesis of no effect can be rejected because the interval does not include zero.
- The drug is harmful.
- The confidence interval is too wide.
- Independent samples t-test.
- Paired t-test.
- Chi-square test.
- One-way ANOVA.
- Paired t-test.
- Chi-square test.
- Independent samples t-test.
- One-way ANOVA.
- It makes it easier to recruit participants.
- It often necessitates a very large sample size to detect a meaningful effect, which can be challenging to achieve.
- Sample size is irrelevant for rare diseases.
- It means the drug will always be effective.
- Simple linear regression.
- Multiple linear regression.
- T-test.
- Chi-square test.
