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MPJE + NAPLEX 2023 PREP > biostat > Flashcards

biostat Flashcards

1
Q

formula for RR

A

relative risk

EER/CER

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2
Q

formula for RRR

A

1 - RR

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3
Q

ARR formula

A

CER - EER

OR

EER - CER

[since this is the absolute value]

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4
Q

NNT formula for the duration of the study

A

1/ARR

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5
Q

NNT for 1 year

A

NNT x (# of years the study was conducted)

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6
Q

odds ratio (OR) formula

A

[EER/ENR] / [CER/CNR]

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7
Q

discrete data

A

generally refers to discrete, countable numbers with no decimals (cannot be divided)

ex: people

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8
Q

continuous data

A

in contract, is more of a continuum in which use of decimals allows for an infinite number of possible values

e: electrolyte levels

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9
Q

discrete data subtypes

A

nominal (categorical) data

ordinal (ranked) data

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10
Q

nominal (categorical) data

A

refers to assigning data to different CATEGORIES based on the occurrence of an outcome

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11
Q

ordinal (ranked) data

A

refers to data that come in a certain order or ranking but the intervals between the values are not necessarily equal

ex: NYHA classification

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12
Q

continuous data subtypes

A

interval data

ratio data

*can be expressed using decimals

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13
Q

interval data

A

refers to measurable data with equal intervals between values. there is no absolute zero

ex: temperature (a “0” temperature has meaning)

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14
Q

ratio data

A

type of data interval that has an absolute zero

ex: height, weight, hemoglobin level

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15
Q

continuous data tests

A

t - test

student’s t test

paired t test

analysis of variance (ANOVA) test

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16
Q

t-test

A

continuous data

means of two groups

ex: cholesterol levels OR HgbA1c

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17
Q

student’s t-test

A

continuous data

two groups are independent and separate

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18
Q

paired t-test

A

continuous data

test group acts as its own control (“PAIRED”)

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19
Q

ANOVA test

A

continuous data

groups of >/= 3 groups are being compared (similar to t-test but there are >/= 3 groups)

CAN BE USED FOR BOTH INDEPENDENT AND PAIRED GROUPS

20
Q

nominal (categorical) data tests

DISCRETE DATA

A

chi-square test

McNemar’s test

Cochran’s Q test

21
Q

chi square test

A

nominal // discrete

two or more independent groups

ex: the risk of GI bleed is compared in ASA group vs placebo group

22
Q

McNemar’s test

A

nominal // discrete

two paired groups

23
Q

Cochran’s Q test

A

nominal // discrete

> /= 3 paired groups

23
Q

ordinal (ranked) data tests

DISCRETE DATA

A

wilcoxon rank sum test

wilcoxon signed rank test

kruskal-wallis test

friedman test

24
Q

wilcoxon rank sum test

A

ordinal // discrete

two independent groups

25
Q

wilcoxon signed rank test

A

ordinal // discrete

two paired groups

26
Q

kruskal-wallis test

A

ordinal // discrete

> /= 3 independent groups

27
Q

friedman test

A

ordinal // discrete

> /= 3 paired groups

28
Q

randomized clinical trial

A

provides high quality statistical test

members of two groups are chosen at random

considered the gold standard

29
Q

cohort studies

A

group (cohort) of people who share a common trait

observed over time

prospective study

outcome of interest is counted or measured

30
Q

case-control studies

A

want to see if drug/effect is back –> looking backwards –> looking at previous cases

choose this when it is unethical to expose patients to a risk factor

CONTROL is different here. means individuals who have never had the outcome or event of interest regardless of their exposure status

GOING BACK IN TIME

31
Q

cross-sectional studies

A

factors and status of group are studied at one specific time (one cross section of time)

looking at PREVALENCE

32
Q

cross-over studies

A

study participants serve as their own control

treatment group will eventually become a control

control group will get the treatment

the two groups are “paired” or “matched”

33
Q

ITT (intent to treat)

A

ALL pt data analyzed (all data that was INTENDED to be studied)

pro = closer to real life

34
Q

PP (per protocol)

A

counts the data only from the pts who COMPLETED the study

pro = more accurate estimate of the drug

35
Q

meta analysis

A

results of many relevant studies are reviewed objectively, quantitatively

want RCTs but need to avoid PUBLICATION BIAS meaning including results from not fancy studies // less exciting studies // studies not published

36
Q

type I error

A

false rejection of the null hypothesis

there is no association but researchers THOUGHT there was an association

association was imagined

saw something that doesn’t exist

alpha = type 1 –> want <0.05 (5%)

means chance of type 1 error is less than 5/100

37
Q

type II error

A

false acceptance of the null hypothesis

there is an association BUT IT WAS MISSED

AGREE WITH NULL BUT THIS IS INCORRECT~!

type II error = beta = 0.20

power = 1 - beta [power increases with increase in sample size AND/OR when the difference of interest between the two groups is more noticeable and/or when the sample size increases]

dont want chance of type II error to be more than 0.20

80% power is the typical MINIMUM power in order for a study to be considered independent

power = likelihood of NOT making a type II error

38
Q

summary of statistical significance

RR
RRR
OR

A

a 95% CI range for ___ that does NOT cross ___ means the study IS statistically significant:

RR; 1
RRR; 0
OR; 1

39
Q

incidence

A

the number of NEW individuals that develop an illness in a given time period (usually 1 year) divided by the total # of individuals at risk during that time

40
Q

prevalence

A

the number of individuals in a population who HAVE an illness divided by the total population

41
Q

relationship between incidence and prevalence

A

prevalence is equal to incidence multiplied by the length of the disease process

if the disease is long term, prevalence is higher than incidence. e.g., HTN

if the disease is short term, incidence is higher than prevalence e.g., meningitis

42
Q

reliability

A

means reproducibility of the results if the test is repeated

43
Q

validity

A

whether a test is assessing what it is supposed to be assessing. two components of validity are sensitivity and specificity

44
Q

sensitivity

A

measures how well a test identifies truly ill people

with a highly sensitive test, a negative result is used to rule OUT the disease

45
Q

specificity

A

measures how well a test identifies or rules out truly well people (without the disease)

a positive result in a highly specific test is used to CONFIRM the disease

MPJE + NAPLEX 2023 PREP (16 decks)

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