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71 Cards in this Set
- Front
- Back
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case control study design
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compare group of people w/ disease to group w/o disease
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case control study measures?
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odds ratio
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cohort study design
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compare group w/ given exposure or risk factor to group w/o
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cohort study measures?
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relative risk
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cross sectional study design
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collect data from grp of people to assess frequency of disease
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cross sectional study measures?
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disease prevalence
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twin concordance study design
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compare frequency twins develop disease
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twin concordance study measures?
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heritability
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adoption study design
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compare siblings raised by biologic vs adoptive parents
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adoption study measures?
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heritability and influence of environment
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Phase I clinical trial
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small # pts (healthy); assess safety, toxicity, pharmokinetics
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Phase II clinical trial
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small # pts w/ disease; assess efficacy, dosing, adverse effects
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Phase III clinical trial
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large # pts randomly assigned to drug or placebo; compare new treatment to standard of care
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Phase IV clinical trial
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post marketing surveillance; detect rare or longterm adverse effects
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meta-analysis
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pools data from several studies to come to overall conclusion; greater power
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Sensitivity definition
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ability to detect disease when present; rule OUT, for screening
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Sensitivity formula
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TP/ TP + FN
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Specificity definition
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ability to test to indicate no disease when disease is not present; rule IN, for confirmation
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specificity formula
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TN / TN + FP
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PPV definition
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probably that person has disease given a (+) test result
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PPV formula
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TP/ TP + FP
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NPV definition
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probably that person is disease free given a (-) test result
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NPV formula
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TN/ FN + TN
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point prevalence
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total cases @ given time / total population
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incidence
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new cases over period / total population at risk
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prevalence is approx equal to?
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incidence x disease duration
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prevalence
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incidence for acute disease
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odds ratio
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odds of disease in exposed group / odds of disease in unexposed group
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odds ratio approximates what? Under what conditions?
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approximates RR if incidence is not too high
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relative risk
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relative probablilty of getting a disease in exposed grp compared to unexposed grp
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relative risk formula
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% disease in exposed grp / % disease in exposed grp
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attributable risk
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difference in risk b/t exposed + unexposed; OR proportion of disease occurrences attibutable to the exposure
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absolute risk reduction (ARR)
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reduction in risk assoc w/ treatment as compabe dto placebo
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NNT
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1/ ARR
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NNH
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1/AR
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Precision
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consistency + reproducibility of a test (reliability); absence of random error
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what reduces precision?
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random error
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accuracy
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trueness of test (validity)
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what reduces accuracy?
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systematic error
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Selection bias
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nonrandom assignment to a study group
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Recall bias
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knowledge of presence of disorder alters recall by subjects
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sampling bias
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subjects are not representative to general population
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late-look bias
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information gathered at inappropriate time
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procedure bias
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subjects in different grps not treated the same
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confounding bias
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effect of 1 factor distorts or confuses effect of the other
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how to control confounding?
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use matching (in case-control studies)
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lead time bias
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early detection confused w/ increased survival
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pygmalion effect
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when researcher's belief in efficacy of a treatment changes outcome of treatment
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Hawthorne effect
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when group being studied changes its behavior ownign to knowledge of being studied
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Positive skew
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mean > median > mode; tail on right
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Negative skew
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mean < median < mode; tail on left
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which is least affected by outliers? Mean, median, or mode
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mode
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Null hypothesis
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no difference
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Alternative hypothesis
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there is a difference
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Type I error
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stating there IS an effect/difference when there really isn't; = p
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Type II error
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stating there IS NOT an effect/difference when there really is; = β
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which error is considered "false positive"? Which is "false negative?"
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false (+) = type I error; false (-) = type II error
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Power, definition
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probability of rejecting null hypothesis when it is in fact false, or likelihood of finding a difference if one in fact exists
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Power depends on?
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1) total # of end points 2) difference in compliance b/t grps 3) size of expect effect
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how to increase power?
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bigger sample size
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power formula
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1-β
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what is n?
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sample size
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what is σ?
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standard deviation; = sqr(variance)
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what is SEM?
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standard error of the mean; = σ/sqr(n); how much variation in mean from sample to sample
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what does it mean if the CI b/t 2 grps overlaps?
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groups are not significantly different
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confidence interval
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range of values in which a specific probability of the means of repeated samples is expect to fall
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t-test
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checks difference b/t means of 2 groups
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ANOVA
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checks difference b/t means of 3 or more groups
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chi squared test
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checks difference b/t 2 or more % or proportions of categorical outcomes
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correlation coefficient r
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b/t -1, 1; closer to 1 = stronger correlation b/t 2 variables
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coefficient of determination
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r^2
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