Biostatistics Flashcards by Joel Glotfelty

Collects data from a group of people to assess frequency of disease (and related risk factors) at a particular point in time

-asks “What is happening?”

Cross-sectional study

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A cross-sectional study can show risk factor association with disease, but does not establish

Causality

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Compares a group of people with a disease to a group of people without a disease

Looks for prior exposure or risk factor
Asks “What happened?”

Case-control study

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Case-control studies measure

Odds ratio

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Compares a group with a given exposure or risk factor to a group without such exposure.

-Looks to see if exposure affects the likelihood of disease

Cohort study

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Asks “Who will develop the disease?

Prospective cohort

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Asks “Who developed the disease? the exposed or unexposed?”

Retrospective cohort

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What type of study would say “Patients with COPD had higher odds of a history of smoking than those without COPD?”

Case-control Study

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What type of study would say “Smokers had a higher risk of developing COPD than nonsmokers?”

Cohort Study

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Compares the frequency with which both monozygotic or both dizygotic twins develop the same disease

-Measures heritability and influence of environmental factors

Twin concordance study

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Compares siblings raised by biological vs. adoptive parents

-measures heritability and influence of environmental factors

Adoption study

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Experimental study involving humans. Compares therapeutic benefits of two or more treatments or of treatment and placebo

-Study quality improves with double blinding and randomization

Clinical Trial

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Refers to the additional blinding of the researchers analyzing the data

Triple-blinding

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Requires a small number of healthy volunteers and asseses safety, toxicity, pharmokinetics, and pharmodynamics

Phase I trial

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Requires a small number of patients with the disease of interest and assesses treatment efficacy, optimal dosing, and adverse effects

Phase II trial

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Requires a large number of patients randomly assigned either to the treatment under investigation or to the best available treatment (or placebo)

-compares new treatment to current standard of care

Phase III trial

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Requires post marketing surveillance of pateints after treatment is approved

detects rare or long-term adverse effects
can result in treatment being withdrawn from market

Phase IV trials

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Sensitivity and specificity are fixed properties of a test, where as PPV and NPV vary depending on

Disease prevalence

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Proportion of all people with the disease who test positive, or the probability that when the disease is present, the test is positive

Sensitivity

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Highly sensitive tests are used for screening in diseases with

Low prevalence

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Desirable for ruling out disease and indicates a low false-negative rate

Highly sensitive test

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Proportion of all people without the disease who will test negative for the disease

Specificity

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Desirable for ruling in a disease and indicates a low false-positive rate

Highly specific test

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How an we remember what sensitive and specific tests are used for?

) Sensitive: SN-N-OUT

2. ) Specific: SP-P-IN

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Used for conformation after a positive screening

Highly specific test

Proportion of positive test results that are true positives

Positive predictive value (PPV)

Proportion of negative results that are true negatives

Negative predictive value (NPV)

High prevalence means what for PPV and NPV?

High prevalence = High PPV and Low NPV

Looks at new cases

Incidence

Looks at all current cases

Prevalence

What is the incidence rate?

new cases / # people at risk

What is the prevalence?

of existing cases / Total # of people

Prevalence is greater than incidence for

Chronic diseases

Odds ratios are typically used in

Case-control studies

Relative risks are typically used in

Cohort studies

The difference in risk between exposed and unexposed groups, or the proportion of disease occurences that are attributable to the exposure

Attributable risk

The proportion of risk reduction attributable to the intervention as compared to a control

Relative risk reduction (RRR)

What is the formula for Relative risk reduction?

1-RR

The difference in risk attributable to the intervention as compared to a control

Absolute Risk Reduction (ARR)

Number of patients who need to be treated for 1 patient to benefit

Number needed to treat (NNT)

Number of patients who need to be exposed to a risk factor for 1 patient to be harmed

Number needed to harm (NNH)

The higher the precision, the higher the

Statistical power (1-β)

Random error decreases the

Precision

Systematic error decreases the

Accuracy

Error in assigning subjects to a study group resulting in an unrepresentative sample -most commonly a sampling bias

Selection bias

What are three types of selection bias?

Berkson bias, healthy worker effect, and non response bias

When the study population selected from the hospital is less healthy then the general population

Berkson bias

When the study population is healthier than the general population

Healthy worker effect

When the participating subjects differ from nonrespondents in meaningful ways

Non-response bias

Awareness of disorder alters recall by subjects -common in retrospective studies

Recall bias

When patients with a disease recall exposure after learning of similar cases

Recall bias

When information is gathered in a systematically distorted manner

Measurement bias

When subjects in different groups are not treated the same

Procedure bias

When the researcher's belief in the efficacy of a treatment changes the outcome of that treatment (aka pygmalion effect)

Observer-expectancy bias

When a factor is related to both the exposure and the outcome but not on the causal pathway -occurs when multiple factors distort or confuse effect of exposure on outcome

Confounding

When early detection is confused with increased survival

Lead-time bias

What are the three measures of central tendency

1. Mean 2. Median 3. Mode

What are the measures of dispersion?

1. Range 2. Variance 3. Standard deviation 4. Standard Error 5. Confidence intervals

What is most effected by outliers? Least effected?

1. Most = mean | 2. Least = mode

How much variability exists from the mean in a set of values

Standard deviation

An estimate of how much variability exists between the sample mean and the true population mean

Standard error of the mean

What are three types of non-normal distributions?

1. bi-modal 2. positive skew 3. negative skew

Suggests two different populations

bimodal data

What are the characteristics of a positive skew?

Mean > median > mode

What are the characteristics of a negative skew?

Mean

Says there is no difference association between the disease and the risk factor

Null hypothesis

Says there is some association between the disease and the risk factor

Alternative hypothesis

Stating that there is an effect or difference when non actually exists

Type I (α ) error (i.e. false positive)

Stating that there is not an effect or difference between the null and alternative hypotheses when one exists

Type II (β) error (i.e. false negative)

There is less than a 5% chance that the data will show something that does not actually exist if

P is less than 0.05

The probability of making a type II error

The probability of rejecting the null hypothesis when it is false

Power (1-β)

Ranges of values within which the true mean of the population is expected to fall, with a specific probability

Confidence interval

What is the z value for 1. 95% CI 2. 99% CI

1. z = 1.96 | 2. z = 2.58

There is no significant difference if the 95% confidence interval for a mean difference between 2 variables includes

Zero

We do not reject the null hypothesis if the 95% CI for OR or RR includes

If the CI's between two groups do not overlap than

Statistically significant difference exists

If the CIs between two groups overlap than

No significant difference exists

Checks differences between means of 2 groups

t-test

Checks differences between means of 3 or more groups

Analysis of Vasiance (ANOVA)

Checks differences between 2 or more percentages or proportions of categorical outcomes (not mean values)

Chi-squared

Is always between +1 and -1. The closer the absolute value is to 1, the stronger the linear correlation between the two variables

Pearson correlation coefficient (r)

What is the coefficient of determination?

r^2

Biostatistics Flashcards

(83 cards)