L23. EBM - Bias, CI

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Questions and Answers

What is a primary outcome of understanding bias in Evidence-Based Medicine (EBM)?

Reduction in the number of studies conducted

Enhanced uniformity in clinical decision-making

Increased acceptance of flawed studies

Improved design and interpretation of research (correct)

Which type of bias results from how a study population is selected?

Attrition bias

Reporting bias

Selection bias (correct)

Measurement bias

Why is recognizing bias crucial for clinicians in EBM?

It helps in interpreting study results more accurately. (correct)

It guarantees that interventions will be successful.

It allows for the dismissal of all findings.

It ensures that all studies report positive results.

What does a confidence interval measure in research?

The precision of an estimate Signup and view all the answers

Which of the following best describes a Type I error?

Incorrectly rejecting a true null hypothesis Signup and view all the answers

What is the result of publication bias in clinical research?

Studies with positive results are preferentially published. Signup and view all the answers

What is one possible effect of poor understanding of bias in EBM?

Misguided clinical practices Signup and view all the answers

Which of the following statistics is used to quantify the power of a study?

Sample size Signup and view all the answers

What is the primary feature of confounding bias?

It distorts the effect of an exposure on an outcome. Signup and view all the answers

How can confounding bias be minimized in studies?

Through randomization and stratification. Signup and view all the answers

What distinguishes effect modification from confounding bias?

Effect modification indicates a biological phenomenon, while confounding does not. Signup and view all the answers

What is an example of lead-time bias?

Patients diagnosed early with colon cancer appear to survive longer without actual improvement. Signup and view all the answers

Why is length-time bias significant in screening tests?

It can lead to an overestimation of survival rates for slowly progressive diseases. Signup and view all the answers

What does publication bias entail?

Studies with positive results are more likely to be published than those with negative results. Signup and view all the answers

What does intention to treat analysis maintain in a clinical trial?

Random allocation of participants to their initial groups. Signup and view all the answers

What is a major limitation of intention to treat analysis?

It may dilute the true effects of an intervention due to participant dropouts. Signup and view all the answers

What strategy is NOT commonly used to correct for confounding bias?

Retrospective analysis exclusively. Signup and view all the answers

What does the median represent in a dataset with an even number of values?

The average of the two middle values. Signup and view all the answers

Which statement is true regarding modes in a dataset?

The mode is the value that occurs most frequently. Signup and view all the answers

What characteristic is NOT associated with a normal distribution?

The distribution has two distinct peaks. Signup and view all the answers

What does the 68-95-99.7 rule describe in a normal distribution?

68% of data falls within one standard deviation. Signup and view all the answers

What is the primary limitation of using the range as a measure of variability?

It focuses only on extreme values. Signup and view all the answers

In a bimodal distribution, what does each peak represent?

The most frequent values in the dataset. Signup and view all the answers

What aspect does the normal distribution signify in terms of data occurrence?

Data near the mean occurs more frequently than data far from the mean. Signup and view all the answers

Which description is false about the mode?

The mode is always the largest value in the dataset. Signup and view all the answers

What defines a non-normal distribution?

It violates the assumptions of normality. Signup and view all the answers

Which statement best explains the primary advantage of nonparametric tests?

They make fewer assumptions about the underlying data. Signup and view all the answers

What is the main purpose of the Chi-Square test in statistical analysis?

To test the association between two categorical variables. Signup and view all the answers

Which of the following statements about p-values is accurate?

P-values help determine if results are likely due to chance. Signup and view all the answers

Which of the following best defines clinical significance?

It assesses whether an effect has practical importance in patient outcomes. Signup and view all the answers

Which of these tests is NOT considered a nonparametric test?

Independent t-test Signup and view all the answers

Which statement best describes the relationship between variance and the data points in relation to the mean?

Lower variance means data points are more closely packed around the mean. Signup and view all the answers

What is the primary purpose of generating confidence intervals?

To estimate where the true value of a statistic may lie. Signup and view all the answers

Which confidence level is most commonly used by convention in statistical analysis?

95% Signup and view all the answers

What role does hypothesis testing play in evidence-based medicine (EBM)?

It provides a framework to evaluate the effectiveness of medical interventions. Signup and view all the answers

What is the null hypothesis (H0) generally indicative of?

There is no statistical difference in a set of observations. Signup and view all the answers

In hypothesis testing, what is typically controlled to minimize inappropriate treatment decisions?

Type I and II errors. Signup and view all the answers

What happens to the confidence interval as the sample size increases?

It narrows as the estimate becomes more precise. Signup and view all the answers

Why is avoiding Type I errors particularly crucial in EBM?

It prevents harmful clinical practices driven by false positives. Signup and view all the answers

Variance is expressed in which of the following units?

Units of the data squared. Signup and view all the answers

Which statement best describes the significance of p-values in hypothesis testing?

They standardize the assessment of whether effects are due to random chance. Signup and view all the answers

Study Notes

Importance of Bias in EBM

Understanding and minimizing bias improves the quality of research by obtaining more accurate results.
Recognizing bias enhances patient care by ensuring better informed treatment decisions.
Bias informs clinicians on how to interpret results and critically evaluate the strength of evidence.
It contributes to transparency and accountability in research by increasing the integrity of the medical literature.

Bias Definitions

Bias is a deviation of results or inferences from the truth.
Bias is introduced during study design, data collection, data analysis, and publication.

Bias - Recruitment & Follow-up

Selection Bias is introduced during patient selection.
Confounding Bias is when a characteristic related to the exposure and outcome distorts the effect of an exposure on an outcome.
Confounding Bias can be minimized through randomization, cross-over studies, matching, and stratification and can be corrected with statistical adjustment.
Lead-Time Bias occurs when early detection appears to increase survival, but the course of the disease remains unchanged.
Length-Time Bias occurs when a screening test detects diseases with a long latency period, while those with a shorter latency become symptomatic faster.

Publication Bias

A.K.A. Study Selection Bias. Research with significant or positive findings are more likely to be published than research with non-significant or negative results.
It is a form of bias that can affect systematic reviews and meta-analyses.

Intention To Treat Analysis

Subjects are analyzed based on their initial group assignment regardless of drop-out or non-adherence.
This approach minimizes the effect of attrition and non-adherence but may dilute the actual intervention effects.

Measures of Central Tendency

Mean.
Median.
Mode.
Range.

Normal Distribution

A.K.A. Gaussian distribution is characterized by symmetrical, bell-shaped curve.
The mean, median, and mode are equal in a perfectly normal distribution.
The 68-95-99.7 rule states that approximately 68% of the data falls within one standard deviation, 95% fall within two standard deviations, and 99.7% fall within three standard deviations.

Non-Normal Distribution

Bimodal distribution has two distinct peaks or modes.
Important in data analysis to recognize as affected by the choice of statistical methods and interpretations, particularly when normality is not met.

Confidence Intervals

A range of values around a calculated statistic for a sample, believed to contain the true value of that statistic within a specific probability.
The larger the sample size, the narrower the range.

Hypothesis Testing

A structured framework used to evaluate the effectiveness of medical interventions.
Guides practitioners to choose treatments backed by statistical evidence.
Controls for type I and type II errors.
Statistical rigor is ensured by setting predefined thresholds (p-values), standardizing the process of determining if observed effects are statistically significant.

Null Hypothesis

Assumes that two possibilities are the same.
There is no statistical difference observed in a set of observations.
This hypothesis is deemed "true" until proven wrong by experimental data.

Nonparametric Tests

fewer assumptions about the underlying data; more robust in cases of non-normality or heteroscedasticity.
Suitable for analyzing ordinal data or non-continuous variables.
Characteristics:
- No normality assumption in the population distribution.
- Capable of handling ordinal, ranked, or categorical data.
- Applicable when sample sizes are small, outliers are present, or the data has non-constant variance.

Example of Nonparametric Tests

Chi-Square: tests the association between two categorical variables.
Fisher’s Exact Test: tests association between two categorical variables in small sample sizes.
Mann-Whitney U test: compares differences between two independent groups; nonparametric equivalent of the t-test.
Wilcoxon signed-rank test: a nonparametric alternative to the paired t-test.
Kruskal-Wallis test: compares three or more independent groups; nonparametric equivalent of ANOVA.

Statistical Significance

Refers to the likelihood that an observed effect in a study is due to something other than chance, typically determined using a p-value.
Helps determine if the results of a study have statistical meaning.
A statistically significant result means there is strong evidence against the null hypothesis suggesting that the observed effect is unlikely to occur randomly.

Clinical Significance

Refers to the practical importance of a treatment effect and the actual benefits to a patient.
Evaluates the effect size and its potential impact on a patient's health or quality of life.

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Description

This quiz explores the critical role of bias in evidence-based medicine (EBM) research. Discover how recognizing and minimizing bias not only improves research quality but also enhances patient care and treatment decisions. Learn about different types of bias and their implications for clinical practice.