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63 Cards in this Set
- Front
- Back
Question
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Answer
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Formula for prevalence?
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Prevalence = (total cases in population at a given time)/(total population)
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Formula for Incidence?
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Incidence =
(NEW cases in population over a given time period)/(total population at risk during that time); *Note: when calculating incidence, don't forget that people peviously positive for a disease are no longer considered at risk. |
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Prevalence is approximately equal to (formula)?
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Prevalence is approx. to incidence * disease duration
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When is prevalence > incidence?
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chronic diseases (e.g., diabetes)
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When is prevalence = incidence?
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acute diseases (e.g., common cold)
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Sensitivity is the number of […] divided by the number of all people with the disease.
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Sensitivity is the number of TRUE POSITIVES divided by the number of all people with the disease.
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Sensitivity is the probability of a […] given that a person has the disease.
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Sensitivity is the probability of a POSITIVE TEST given that a person has the disease.
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Specificity is the number of […] divided by the number of all people without the disease.
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Specificity is the number of TRUE NEGATIVES divided by the number of all people without the disease.
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Specificity is the probability of a […] given that a person is free of the disease.
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Specificity is the probability of a NEGATIVE TEST given that a person is free of the disease.
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The false […] rate is equal to 1-sensitivity.
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The false NEGATIVE rate is equal to 1-sensitivity.
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The false […] rate is equal to 1-specificity.
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The false POSITIVE rate is equal to 1-specificity.
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Formula for PPV?
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PPV = a/(a+b)
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Formula for NPV?
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NPV = d/(c+d)
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Formula for sensitivity?
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sensitivity = a/(a+c)
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Formula for specificity?
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specificity = d/(b+d)
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Number of true positives divided by the number of people who tested positive for the disease?
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Positive Predictive Value (PPV)
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The probability of having a condition given a positive test?
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Positive Predictive Value (PPV)
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The number of true negatives divided by the number of people who tested negative for the disease?
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Negative Predictive Value (NPV)
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The probability of not having the condition given a negative test?
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Negative Predictive Value (NPV)
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Unlike sensitivity and specificity, predictive values are dependent on the […] of the disease.
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Unlike sensitivity and specificity, predictive values are dependent on the PREVALENCE of the disease.
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Odds Ratio (OR)?
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Odds of having disease in exposed group divided by odds of having disease in unexposed group.
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For Odds Ratio, odds are calculated […] as the number with disease divided by the number without disease.
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For Odds Ratio, odds are calculated WITHIN A GROUP as the number with disease divided by the number without disease.
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In what situation does Odds Ratio (OR) approximate Relative Risk?
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if prevalence of disease is not too high.
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Odds Ratio is used for […] studies.
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Odds Ratio is used for CASE-CONTROL studies.
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Formula for Odds Ratio?
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OR = (a*d)/(b*c)
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Formula for Relative Risk?
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RR = a/(a+b) divided by c/(c+d)
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Formula for Attributable Risk?
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AR = a/(a+b) minus c/(c+d)
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Relative Risk (RR)?
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Disease risk in exposed group divided by disease risk in unexposed group.
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Risk is calculated […] as the number with disease divided by the total number of people in the group.
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Risk is calculated WITHIN A GROUP as the number with disease divided by the total number of people in the group.
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Relative Risk (RR) is used for […] studies.
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Relative Risk (RR) is used for COHORT studies.
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To commit a Type I error (alpha) is to state what?
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There IS an effect or difference when none exists (to mistakenly accept the experimental hypothesis and reject the null hypothesis).
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p is judged against […], a preset level of significance (usually < 0.05).
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p is judged against alpha, a preset level of significance (usually < 0.05).
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p = ?
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p = probability of making a type I error.
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If p < 0.05, then there is less than a 5% chance that […].
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If p < 0.05, then there is less than a 5% chance that THE DATA WILL SHOW SOMETHING THAT IS NOT REALLY THERE.
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Layman's way of describing alpha?
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alpha = you "saw" a difference that did NOT exist--for example, convicting an innocent man.
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In a four quadrant box, power lies in what region?
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Power is at the intersection of column H1 (reality) and row H1 (study results)
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In a four quadrant box, alpha lies in what region?
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Alpha is at the intersection of column H0 (reality) and row H1 (study results)
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In a four quadrant box, beta lies in what region?
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Beta is at the intersection of column H1 (reality) and row H0 (study results)
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To commit a Type II error (beta) is to state what?
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There is NOT an effect or difference when one exists (to fail to reject the null hypothesis, when, infact H0 is false).
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Beta is the probability of making a type […] error.
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Beta is the probability of making a type II error.
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Layman's way of describing beta?
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Beta = you did not "see" a difference that does exist--for example, setting a guilty man free.
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Qualitative definition of Power?
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Power is the probability of rejecting the null hypothesis when it is, in fact, false.
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Power depends upon what (3 items)?
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1. Total number of end points experienced by population.
2. Difference in COMPLIANCE b/w treatment groups (differences in the mean values b/w groups). 3. Size of expected effect. |
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If you […] sample size, you increase Power.
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If you INCREASE sample size, you increase Power. There is Power in numbers.
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Formula for SEM?
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SEM = SD/(square root of sample size)
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SEM […] SD?
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SEM < SD?
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SEM […] as sample size increases?
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SEM DECREASES as sample size increases?
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For a Normal (Gaussian) distributional curve, SD of 1 = x%?
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SD 1 = 68%
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For a Normal (Gaussian) distributional curve, SD of 2 = x%?
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SD 2 = 95%
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For a Normal (Gaussian) distributional curve, SD of 3 = x%?
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SD 3 = 99.7%
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CI = range from […] to […]?
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CI = range from [mean - Z(SEM)] to [mean + Z(SEM)]
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The 95% CI corresponds to what p value?
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p = 0.05
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For the 95% CI, Z = […].
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For the 95% CI, Z = 1.96.
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If the 95% CI for a […] between 2 variables includes 0, then there is no significant difference and H0 is NOT rejected.
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If the 95% CI for a MEAN DIFFERENCE between 2 variables includes 0, then there is no significant difference and H0 is NOT rejected.
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If the 95% CI for […] or […] includes 1, then H0 is NOT rejected.
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If the 95% CI for ODDS RATIO or RELATIVE RISK includes 1, then H0 is NOT rejected.
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Chi squared checks what?
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difference b/w 2 or more percentages or proportions of categorical outcomes (NOT mean values).
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Chi squared =
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compare percentages (%) or proportions
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r squared =
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Coefficient of determination
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Mnemonic for reportable diseases IN ALL STATES?
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"B.A. S.S.S.M.M.A.R.T. Chicken or you're Gone:"
Hep B Hep A Salmonella Shigella Syphilis Measles Mumps AIDS Rubella TB Chickenpox Gonorrhea |
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Which disease can vary by state for reporting?
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HIV
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Medicare Part A =
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hospital
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Medicare Part B =
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doctor bills
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