# BEHAVIORAL SCIENCE

rename
laracrystalo's
version from
2016-07-17 21:29

## Section

Question | Answer |
---|---|

PPV and prevalence association? | PPV increases with increasing disease prevalence and decreases with decreasing disease prevalence |

NPV and prevalence association? | NPV decreases with increasing disease prevalence and increases with decreasing disease prevalence |

type I error | alpha. rejecting the null hypothesis when it is actually true |

type II error | beta. accepting the null hypothesis when it is actually false |

P < alpha | ideal, this is statistically significant and means rejecting the null |

P > alpha | fail to reject the null hypothesis |

R = 1 | perfect correlation |

R = 0 | no correlation at all |

R > 0 | + correlation so positive slope |

R < 0 | - correlation so negative slope |

1 standard deviation | 68% |

2 standard deviations | 95% |

3 standard deviations | 99.7% |

how does a larger sample size affect power? | increases power |

how does a larger sample size affect Confidence Interval? | decreases confidence interval |

precision is akin to | reliability |

accuracy is akin to | validity |

what factors make something reproducible? | precision and reliability |

what factors make something compared to the gold standard | accuracy and validity |

standard error of mean | SD / sq rt of sample size |

confidence interval | mean +/- Z (SEM) |

Z value? | 1.96 for 95% ; 2.58 for 99% |

incidence | number of new cases / number at risk |

prevalence | number of existing cases / total population |

positive skew | mode < median < mean (R skew) |

negative skew | mode > median > mean (L skew) |

which study type looks at odds ratio? | case control |

what does case control find? | odds ratio |

what studies find relative risk? | RCT or cohort |

what do cohort studies find? | relative risk |

what do RCT studies find? | relative risk |

what do cross sectional studies find? | disease prevalence |

what studies find disease prevalence? | cross sectional |

snap-shot in time | cross sectional |

no controls | case series |

when prevalence is low, what happens to OR and RR? | they become more equal |

how do you increase precision? | decrease standard deviation and increase statistical power |

most affected by outliers? | mean |

least affected by outliers? | mode |

primary disease prevention | prevent (vaccination, condoms) |

secondary disease prevention | screening (pap) |

tertiary disease prevention | treatment (chemo) |

phase I trial | toxicity, safety, pharm dynamics and kinetics |

phase II trial | efficacy, dosing, adverse effects |

phase III trial | compare to standard |

phase IV trial | long term adverse effects |

NNT | 1/ARR |

NNH | 1/AR |

OR | (a/c) / (b/d) OR ad/bc |

RR | a/a+b / c/c+d |

AR | a/a+b - c/c+d |

ARR | c/c+d - a/a+b |

failure of precision | random error |

failure of accuracy | systematic error |

reproducibility of test results | precision aka reliability |

the test measures what it is supposed to | accuracy aka validity |

## BIAS

Question | Answer |
---|---|

study population selected form hospital is less healthy than general population | berkson bias (selection bias) |

study population is healthier than general population | healthy worker effect (selection bias) |

participating subjects differ from nonrespondents in meaningful ways | non-response bias (selection bias) |

awareness of disorder alters recall by subjects | recall bias |

common in retrospective studies | recall bias |

information is gathered in a way that distorts it | measurement bias |

subjects in different groups are not treated the same | procedure bias |

researchers belief in the efficacy of treatment changes the outcome | pygmalion effect (observer-expectancy bias) |

factor is related to both exposure and outcome | confounding bias |

early detection is confused with increased survival | lead time bias |

reduce selection bias? | randomization |

reduce recal bias? | decrease time from exposure to follow up |

reduce measurement bias? | use standardized method of data collection |

reduce procedure bias or pygmalion effect? | blinding and placebos |

reduce confounding bias? | multiple repeated studies, crossover studies, matching |

reduce lead time bias? | measure back-end survival |

change in behavior in a study group resulting from knowing they are being observed | hawthorn effect |

what does matching patients control for? | confounding |

## Recent badges

## Pages linking here (main versions and versions by same user)

No other pages link to this page. See Linking Quickstart for more info.