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55 Cards in this Set

  • Front
  • Back
Mean
average
Median:
middle value
Mode:
most frequent value
Endemic:
localized epidemic
Pandemic:
world-·wide epidemic
which of the following central tendency measures is sensitive to outliers?
mean
which of the following central tendency measures is used in a skewed population?
median
Variability:
what are the different standard deviations and their percentage?
1 STD: 68%
2 STD: 95%
3 STD: 99%
Chi square
compare percentages
T -test
compare 2 things
ANOVA
compare 3+ things
Skewing:
shift to right (mean> median > mode)
Standard Error of Mean
= S/ (square root) of N => precision of mean
S = standard deviation, N = sample size
1 -> 2 Question Survey:
what will happen to sensitivity? NPV? specificity? and PPV?
Decrease: Sn, NPV
Increase: Sp, PPV
PPV
equation
effect on prevalence
example
= TP / all positives
(increases w / prevalence)
Ex: ( +) ELISA -> Do you have HIV?
NPV
equation
define
= TN/ all negatives
(probability of not having a dz if have negative test)
Sensitivity
= a/ a+c = TP /all diseased (people that have dz)
Specificity
= d/ b +d = TN/ all non-diseased (people that don't have dz) "
Incidence
equation
= new cases/ total population
Prevalence= equation
example
= all diseased/ total population
(Ex: improved quality of care)
Odds Ratio= equation
what does it mean in layman's terms
• OR <1 =>
• OR >1 =>
Odds Ratio= (ad+ bc) cross product
(diseased are x times more likely to see risk factor)
• OR <1 => protective factor
• OR >1 => risk factor
Correlation Coefficient:
• 0:
• +:
• -:
• 0: nothing
• +:correlation
• -: negative correlation
CI
= 95% => 95% sure it lies within the interval (cannot include 1.0)
RR= equation
explain in layman's terms
= exposed/ unexposed
(risk of getting dz w/ known exposure)
define NNT
p value < 0.5
= number needed to treat to change 1 life
p value < 0.5 = random chance that you will be wrong 1 time out of 20
Null hypothesis
=> nothing's happening
Power:
equation
explain in layman's terms
1-β = probability of detecting a true intervention
what is improved by ⇧size of study
power
Effect size
= how different two groups are
α type I error
(FN), P value error "too optimistic''
β: type II error
(FP), Power error "too pessimistic"
what is the cause of type β: type II error?
small samples
Prevention:
1°:
2°:
3°:
Prevention:
1°: ⇩Incidence
2°: ⇩Prevalence
3°: Slows disease progression
Accuracy:
validity "truth"
Precision:
reliability "keep making the same mistake"
Admission rate:
hospitals have certain populations
Confounding bias:
define
what are the 3 things that should be done to prevent this
forgotten variable => use matching, restriction, randomization
Lead time:
time between diagnosis and treatment
Hawthorne effect:
the "watched" change their behavior
Unacceptability:
subjects lie
Observer bias:
the observers have knowledge about control and study samples
Recall bias:
inaccurate recall of past events
Respondant:
subjective diagnosis
Sample distortion:
sample does not represent population
Selection
who is in or out
I) Clinical Trials: experimental
Phase I:
Phase II:
Phase III:
Phase IV:
Phase I: Toxicity "burt pt?"
Phase II: Efficacy "help pt?"
Phase III: Comparison "any better?"
Phase IV: Post-marketing surveillance "can they screw it up?"
Cohort study:
define
what happens in a cohort study?
what does it determine?
Prospective
Observe a "cohort" (group of people with similar characteristics) to see how many develop a specific
disease after exposure to a risk factor.
• Determines incidence: new cases of disease
Cohort study:
what risk it uses
occurs where
ex
• Uses Relative Risk
• Occurs in community
• Ex: finds new cases of common disease
Case control:
type of study
what happens in a case control
what does it use?
where does it occur?
bias
examples
Retrospective
• Select subjects with a disease, compare to controls, and study the differences
• Uses Odds Ratio
• Occurs in hospital
• Has more selection bias
• Ex: finds risk of developing rare disease
Cross sectional:
define
what does it determine
example
snaphot in time
• Determines prevalence: total cases of diseased
• Ex: polls/ surveys
Case report
describe an unusual pt
Case series report
describe several unusual pts
Consensus panel
panel of experts provides a recommendation
Clinical wisdom
"I think .... "
Meta-Analysis
tries to combine data from many trials