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Biostats and epidemiology > Biostats and epidemiology > Flashcards

Biostats and epidemiology Flashcards

1
Q

Definition of type 1 error (alpha error)

A

Rejecting the null hypothesis when it is really true

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2
Q

Definition of a type 2 error (beta error)

A

Not rejecting the null hypothesis when it is really false

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3
Q

Ways to increase statistical power

A
  • Increase the sample size (most common)
  • Increase the expected effect size
  • Increase precision of measurement
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4
Q

Use of the t-test

A

Comparing the means of two groups from a single nominal variable, using means from an Interval variable to see whether the groups are different

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5
Q

Use of one-way ANOVA

A

Compares means of many groups (2 or more) of a single nominal variable using an interval variable

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6
Q

Use of chi squared

A

Tests to see whether two nominal variables (not mean) are independent

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7
Q

Infectious diseases that require mandatory reporting to the local Public Health Department, who will inform the CDC

A

“Salas siente comezón, grita y chilla al horinar”

  • Chlamydia
  • Gonorrhea
  • Chicken pox
  • AIDS
  • Syphilis
  • Salmonella
  • Hepatitis A and B
  • Tuberculosis
  • Lyme disease
  • Other: pertussis, legionnaires, mumps, rubella and measles
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8
Q

Coverage of Medicare

A
  • Ambulance transport
  • Dialysis
  • Speech and occupational therapy
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9
Q

Data analysis test used in cross-sectional studies

A

Chi-squared

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10
Q

Data analysis test used in case-control studies

A

Odds ratio

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11
Q

Data analysis test used in cohort studies

A

Relative risk

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12
Q

Describe the sample size, data evaluated, and duration of phase 1 clinical trials

A
  • Sample size: 20 to 100 (healthy)
  • Data evaluated: safety, toxicity, pharmacokinetics/pharmacodynamics, adverse effects
  • Duration: 1 to 30 days

“Is it SAFE?”

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13
Q

Describe the sample size, data evaluated, and duration of phase 2 clinical trials

A
  • Sample size: 100 to 300 (disease)
  • Data evaluated: dose, tolerability, efficacy, adverse effects
  • Duration: months

“Does it WORK?”

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14
Q

Describe the sample size, data evaluated, and duration of phase 3 clinical trials

A
  • Sample size: 100s to 1000s
  • Data evaluated: compares the new treatment to the current standard of care
  • Duration: months to years

“Any IMPROVEMENT?”

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15
Q

Describe the sample size, data evaluated, and duration of phase 4 clinical trials

A
  • Sample size: 1000s
  • Data evaluated: epidemiology, postmarketing surveillance, common and rare side effects
  • Duration: years

“MARKET”

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16
Q

Define sensitivity

A

Proportion of truly diseased persons in the screened population who are identified as diseased by the screening test (“true positive rate”)

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17
Q

Define specificity

A

Proportion of truly disease-free persons who are identified as non-diseased by the screening test (“true negative rate”)

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18
Q

Define positive predictive value

A

Probability that a person with a positive test is a true positive

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19
Q

Define negative predictive value

A

Probability of no disease in a person with a negative test

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20
Q

Define accuracy

A

Degree to which a measurement, or an estimate based on measurements, represents the true value of the attribute that is being measured

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21
Q

Formula for odds ratio

A

OR = AD/BC

*La probabilidad de que los que estuvieron expuestos desarrollen la enfermedad sobre la probabilidad de que los que no estuvieron expuestos desarrollen la enfermedad ((A/B)/(C/D))

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22
Q

Formula for relative risk

A

RR = (A/A+B)/(C/C+D)

*La incidencia de la enfermedad en los que estuvieron expuestos sobre la incidencia de la enfermedad sobre los que no estuvieron expuestos

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23
Q

Define the attributable risk

A

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

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24
Q

Formula of attributable risk

A

AR = (A/A+B) - (C/C+D)

*La incidencia de la enfermedad en los que estuvieron expuestos menos la incidencia de la enfermedad en los que no estuvieron expuestos

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25
Q

Define a selection bias

A

When the sample is not representative (nonrandom smapling or treatment allocation of subjects)

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26
Q

Examples of selection biases

A
  • Berkson bias
  • Non-response bias
  • Healthy worker effect
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27
Q

Define the berkson bias

A

Study population selecten from hospital is less healthy than general population

28
Q

Define the non-response bias

A

Participating subjects differ from nonrespondents in meaningful ways

29
Q

Define the healthy worker effect

A

Study population is healthier than the general population

30
Q

Solutions to a selection bias

A
  • Randomization

* Ensure the choice of the right comparison/reference group

31
Q

Define a measurement bias

A

Information is gathered in a systemically distorted manner

32
Q

Define the Hawthorne effect

A

Measurement bias in which participants change their behavior in response to their awareness of being observed

33
Q

Solution to a measurement bias

A
  • Using objective, standardized and previously tested methods of data collection
  • Using control/placebo groups (Hawthorne)
34
Q

Define an expectancy bias

A

Researcher’s beliefs affect outcome (aka Pygmalion effect)

35
Q

Solution to an expectancy bias

A

Double-blind design

36
Q

Solution to a lead-time bias

A

Measure “back-end” survival (adjust survival according to the severity of disease at the time of diagnosis)

37
Q

Solution to a recall bias

A
  • Decrease time from exposure to follow-up

* Multiple sources to confirm information

38
Q

Define a confounding bias

A

Unanticipated factors obscure results (a factor is related to both the exposure and the outcome)

39
Q

Solution to a confounding bias

A
  • Multiple/repeated studies
  • Crossover studies
  • Matching
  • Restriction
  • Randomization
40
Q

Formula for standard error

A

SE = SD/square root of the samples

41
Q

Define the nested case-control design

A

Study starts with cohort study, and those who develop an outcome of interest become cases for a case-control study

42
Q

Black box warnings are added during which phase of the clinical trial

A

Phase 4

43
Q

Most important characteristic of an ecological study

A

Unit of analysis is populations, not individuals

44
Q

What is an ecollogical fallacy

A

Making conclusions regarding individuals within populations

45
Q

Describe a crossover study

A

Subjects are randomly allocated to a sequence of 2 or more treatments given consecutively

46
Q

Advantage of a crossover study

A

It allows patients to serve as their own controls

47
Q

Disadvantage of a crossover study

A

Effects of one treatment may carry over and alter response to a subsequent treatment

48
Q

Solution to the drawback of a crossover study

A

Have a washout phase

49
Q

Formula for relative risk reduction

A

RRR = 1 - RR

50
Q

Formula for absolute risk reduction

A

ARR = (C/C+D) - (A/A+B)

51
Q

Formula for number needed to treat

A

NNT = 1/ARR

52
Q

Formula for number needed to harm

A

NNH = 1/AR

53
Q

Define precision

A

The consistency and reproducibility of a test

54
Q

Methods to increase precision

A
  • Decrease standard deviation

* Increase statistical power

55
Q

Formula of attack rate

A

Number of individuals who become ill divided by the number of individuals who are at risk of contracting the illness

56
Q

Define an attrition bias

A

Lose to follow up occurs disproportionately between exposed and unexposed groups

57
Q

Difference between effect modification and confounding bias

A

Effect modification refers to when the effect of an exposure on an outcome is modified by another variable

58
Q

What should you do to differentiate between effect modification and confounding bias

A

Stratified analysis (stratification is based on the confounder, if association disappears, it is a confounding bias)

59
Q

Formula for the CI for a population mean

A

CI = mean +/- Z(SE)

60
Q

Z values for a 95% CI and 99% CI

A
  • 95% = 1.96

* 99% = 2.58

61
Q

Define a late-look bias

A

Survey doesn´t uncover patients with severe disease because they die first

62
Q

Define a proficiency bias

A

When the different skill levels of physicians delivering treatment might affect patient outcomes more than the treatment selection itself

63
Q

Disorders related to a high socioeconomic status (SES)

A
  • Anxiety disorders
  • Breast cancer
  • Bipolar disorders
64
Q

Definition of socioeconomic status

A

Weighted combination of education and occupation status

65
Q

Formula for accuracy

A

(TP + TN)/Everything

66
Q

Leading causes of death overall in the US (top 3)

A
  1. Heart disease
  2. Cancer
  3. Unintentional injuries
67
Q

Age group in which suicide is the number 2 cause of death

A

10 - 34 years old

Biostats and epidemiology (1 decks)

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