Statistics Flashcards

1
Q

Sensitivity definition

A

true positive rate proportion of all people with the disease that test (+) for disease when disease is present values approaching 100% desirable for ruling out disease

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2
Q

Sensitivity equation

A

= TP / (TP + FN) = 1 - (false negative rate)

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3
Q

specificity definition

A

true negative rate proportion of people without the disease who test (-) values approaching 100% desirable for ruling in disease

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4
Q

specificity equation

A

= TN / (FP + TN) = 1 - (false positie rate)

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5
Q

positive predictive value definition

A

proportion of positive test results that are true positives

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6
Q

positive predictive value equation

A

= TP / (TP + FP)

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7
Q

negative predictive value definition

A

proportion of negative test results that are true negative

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8
Q

negative predictive value equation

A

= TN / (TN+ FN)

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9
Q

Incidence looks at the number of _____ cases in a SPECIFIC period of time

A

new cases

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10
Q

prevalence looks at _____ cases in a SPECIFIC period of time

A

all existing cases

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11
Q

incidence equation

A

incidence rate = (# of new cases in a specific time period)/ (population at risk during same time period)

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12
Q

prevalence equation

A

prevalence = (# of existing cases) / (population at risk) approximately equal to (incidence rate) X (average disease duration)

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13
Q

Risk / disease ratio table

A

Disease

+ -

risk factor + a b

                           -        c                  d
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14
Q

odds ratio

  • study used in
  • definition
A

case control studies

odds that the group with the disease (cases) was exposed to a risk factor (a/c) **divided by **the odds that the group without the disease (controls) was exposed (b/d)

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15
Q

odds ratio equation

A

= (a/c) / (b/d)

= ad/ bc

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16
Q

relative risk

  • study used in
  • definition
A

cohort study

risk of developing disease in exposed group **divided by ** risk in the unexposed group

17
Q

relative risk equation

A

= (a/(a+b)) / (c/(c+d))

18
Q

attributable risk definition

A

difference in risk between exposed and unexposed groups

or

the proportion of disease occurence that are attributable to the exposure

19
Q

attributable risk equation

A

= (a / (a+b)) - (c/(c+d))

20
Q

absolute risk reduction equation

A

ARR = (control event risk) - (experiment event rate)

21
Q

number needed to treat

  • definition
  • equation
A

number of patients who need to be treated for 1 patient to benefit

= 1/ ARR

22
Q

number needed to harm

  • definition
  • equation
A

number of patients who need to be exposed to a risk factor for 1 patient to be unharmed

= 1/ attributable risk

23
Q

Standard error of Mean (SEM) =

A

(standard deviation) / (square root of sample size)

as sample size increases, standard error of mean decreases

24
Q

normal distrubtion

A

bell shaped curve (gaussian)

mean = median = mode

25
Q

positive skew vs. negative skew

A

positive: mean > median > mode

asymmetry with longer tail on right

negative: mode > median > mean

asymmetry with longer tail on left

26
Q

Null hypothesis (Ho)….. hypothesis of no difference

Alternative (H1)… hypotheis of some difference

chart

A

reality

H1 Ho

study result H1 power (1 - beta) alpha

                          Ho     beta             correct
27
Q

Type I error (alpha)

A

accept alternative and reject null hypothesis

states that there is an effect or difference when none exists

if P < .05

-there is a 5% chance that the data will show something that is not really there

28
Q

type II error (beta)

A

accept null… reject alternative hypothesis

stating that there is not an effect or difference when one exists

false negative

29
Q

power (1- beta)

A

probability of rejecting null hypothesis when it is in fact false

or

the likelihood of finding a difference if one in fact exists

30
Q

Confidence interval equation

A

CI = [mean - Z(SEM)] to [mean + Z(SEM)]

SEM = standard error of mean

Z = Z-score

for the 95% CI: z = 1.96

for the 99% CI: z = 2.58

31
Q

if 95% CI for a mean difference between two variables includes 0, then there is _____ difference and Ho is _____

A

no significant difference

Ho is not rejected

32
Q

if the 95% CI for odds ratio or relative risk includes 1, Ho is ____

A

not rejected

33
Q

If the CIs between 2 groups do not overlap, then ____

if the CIs between two groups do overlap, then ____

A

do not: significant difference exists

do: usually not significant difference exists

34
Q

test that checks for the difference between the means of **two **groups

A

T-test

35
Q

test that checks difference between means of 3 or more groups

A

ANOVA

(analysis of variance)

36
Q

test checks difference between two or more percentages or proportions of categorical outcomes (not mean values)

A

chi-square (X2)

compares percentages or proportions

37
Q

Parson’s correlation coefficient (r)

A

r is always between -1 and +1

closer the absolute value of r is to 1: the stronger the linear correlation between two variables

coefficient of determination = r2