Study biases and Hypothesis testing Flashcards
What is selection bias?
Nonrandom assignment to participate in a study group.
Most commonly a sampling bias.
What kind of bias may be present in a study with many patients who are “lost to follow up”?
A selection bias - the disease may have early mortality, leading to a loss of certain participants.
What kind of bias may be present in a study with healy workers and volunteers?
Selection bias - Study populations are healthier than general population.
How can selection bias be reduced?
Randomization
Ensure the choice of the right comparison/reference group.
What is recall bias?
Awareness of disorder alters recall by subjects - common in retrospective studies.
Patients with disease recall exposure after learning about similar cases.
How can you reduce recall bias?
Shorten the time from exposure to follow-up.
What is measurement bias?
Information gathered in a way that distorts it.
Example: Hawthorne effect - groups who know they’re being studied behave differently.
What is procedure bias?
Subjects in different groups are not treated the same.
What is observer-expectancy bias?
Researcher’s belief in the efficacy of the treatment changes the outcome of that treatment.
Example: If observer expects treatment group to show signs of recovery, more likely to document positive outcomes.
How can measurement, procedure, and observer-expectancy bias be reduced?
Use of placebo control groups with blinding to reduce influence of participants and researchers on experimental procedures and interpretation of outcomes.
What is a confounding bias?
When a factor is related to both the exposure and outcome but not on the causal pathway.
Factor distorts or confuses effect of exposure on the outcome.
Example: Pulmonary disease is more common in coal miners than general population. However, coal miners are also more likely to smoke than the general population.
How can confounding bias be reduced?
Multiple/repeated studies.
Crossover studies (subjects act as own controls)
Matching (patients with similar characteristics in both treatment and control groups)
What is lead-time bias?
Early detection is confused with longer survival, seen with improved screening techniques.
Early detection makes it seem as though survival has increased, but the natural history of the disease is unchanged.
How can lead-time bias be reduced?
Measure “back-end” survival (adjust survival according to severity of disease at time of diagnosis).
What are the measures of central tendency?
Mean, median, and mode.
What is the definition of the mean, median, and mode?
Mean = (sum of values) / (total number of values)
Median = middle value of a list of data sorted from least to greatest
Mode: The most common value.
If there is an even number of values, the median will be the average of the middle two values.
What is standard deviation?
Stanrdard deviation = how much variability exists from the mean in a set of values.
What is the standard error of the mean?
How is it calculated?
SEM = an estimate of how much variability exists between the sample mean and the true population mean.
SEM - SD / (square root [n])
Where SD = standard devaition and n = sample size.
Thus, SEM decreases as n increases.
How is the shape of a normal distribution described?
In a normal distribution, how many of the values are one standard deviation away from the mean?
How about two?
Three?
Gaussian/bell shaped.
1SD from the mean: 68%
2SD: 95%
3SD: 99.7%
How is a bimodal distribution shaped, and what does it suggest?
Bimodal: Two peaks (two values with high frequency)
Suggests two different populations are being measured.
How is a positively skewed distribution shaped?
What will the relative size of the mean, median, and mode be?
Asymmetry with a longer tail on the right.
Typically Mean > median > mode
How is a negatively skewed distribution shaped?
What will the relative size of the mean, median, and mode be?
Asymmetry with a longer tail on the left.
Typically mean < median < mode
What are the null and alternative hypotheses?
Null hypothesis: There is no difference
Alternative hypothesis: There is some difference
What is type I error? What greek letter represents it?
α = probability of type I error
Stating that there is an effect or difference when none exists (null hypothesis incorrectly rejected in favor of alternative hypothesis).
AKA false positive error.
A p-value is judged against a preset α level of significance (usually < .05). If p < .05 there is less than 5% chance that the data will show something that is not really there.
α = you saw a difference that did not exist (e.g., convicting an innocent man).
