Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

NAPLEX review 2024 RXPrep Book > Biostatistics > Flashcards

Biostatistics Flashcards

1
Q

two types of continuous data

A

Ratio and interval data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Ratio data

A

equal difference between values, with a true meaningful zero
0 = none

example: age, height, weight, time, BP

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Interval data

A

equal difference between values, but without a meaningful zero
0 doesnt equal none

example: temp

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

two types of Discrete (Categorical) data

A

nominal and ordinal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Nominal data

A

sorted into arbitrary categories

males/females

known as yes/no data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

ordinal data

A

ranked and has a logical order

ie. pain scale, 1-10

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Which data is mean preferred

A

continuous data that is normally distributed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Which data is median preferred

A

continuous data that is no normal distributed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Which data is mode preferred

A

nominal data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Percent of values within 1 SD? 2 SD?

A

1 SD = 65%
2 SD = 95%

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

When do you often see skewed distribution

A

sample size is small
outliers in data

by collecting more values, effect of outliers is decreased

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Independent vs dependent variable

A

Independent = changed (manipulated) by researcher to determine if it as affect on the dependent variable (outcome)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

null hypothesis

A

states that there is no statistically significant deference between groups

researchers want to reject it to show that their drug/product is statistically different

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Alternative hypothesis

A

states that there is a statistically significant difference between the groups

what the researcher hopes to prove or accept

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Alpha

A

maximum permissible error margin
Alpha is the threshold for rejecting the null hypothesis
commonly set to 0.05 or 5%

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Comparing p-value to alpha

A

if alpha set to 0.05, and p-value is less than then null hypothesis is rejected and result is statistically significant

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

How to tell if something is statistically significant with CI and without p-value

A

if crosses zero = not statistically significant

if doesnt cross zero = statistically significant

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

How to tell if something is statistically significant if it has ratio data

A

if crosses 1 = not statistically significant

if doesnt cross 1 = statistically significant

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Narrow vs Wide Confidence interval

A

Narrow = high precision
Wide = lower precision

narrow is preferred

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Type 1 error

A

False positive

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

The probability of making a type 1 error relates to….

A

the alpha

if alpha is 0.05 and p < 0.05, then probability of error is < 5%, 95% confident that result is correct

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Type 2 error

A

False negative

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

The probability of making a type 2 error relates to….

A

beta

usually set to 0.1 or 0.2, meaning 10%-20%

type 2 error increases with smaller sample sizes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

Study power is….

A

the probability that a test will reject the null hypothesis correctly

ie. power to avoid type 2 error

power = 1- beta

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

Power is determined by….

A

number of outcome values collected, difference in outcome rates between groups and significance (alpha) lvl

larger sample size = increases study power

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

Relative risk (Risk ratio) is….

A

ratio of risk in exposed group (txm) divided by risk in control group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

Risk is….

A

number of subjects in group with an unfavorable event / total number of subjects in group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

Risk Ratio is…

A

risk in txm group / risk in control group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

Risk Ratio interpretation

A

RR =1 = no difference in risk of outcome between groups
RR > 1 = greater risk of outcome in txm group
RR < 1 = lower risk (reduced risk) of outcome in txm group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

Relative risk reduction….

A

indicates how much the risk is reduced in the txm group compared to the control group

1 - Risk Ratio = RRR

31
Q

RRR interpretation of 43%

A

XXXXX patients were 43% less likely to have YYYYY than placebo-treated patients

32
Q

Absolute risk reduction

A

includes the reduction in risk and incidence rate of the outcome

ARR = % risk in control group - % risk in txm group

33
Q

ARR interpretation of 12%

A

12 out of every 100 patients will benefit from txm
or
For every 100 patients tx with XXX, 12 fever will have YYYYY

34
Q

Number needed to treat

A

number of patients who need to be treated for a certain period of time for one patient to benefit

1/ ARR

35
Q

Number needed to treat interpretation, NNT = 9

A

For eery 9 pts who receive XXX, YYYY is prevented in 1 patient

36
Q

Number needed to harm

A

number of patients need to be treated for one patient to experience harm

same formula, 1/ ARR

37
Q

Number needed to harm interpretation, NNH = 90

A

1 patient will be harmed for every 90 patients treated with XXX instead of placebo

38
Q

Which studies are not suitable for relative risk calculations

A

Case control studies

use Odds ratio

39
Q

Odds Ratio formula

A

Present | A | B. |
——————————————————————————–
Absent. |. C. |. D. |

Formula = AD/ BC

40
Q

Interpreting Odds ratio of 1.23

A

XXXXXX is associated with 25% increased risk of YYYYYY

41
Q

Hazard ratio

A

used in survival analysis instead of using “risk”

Hazard rate is rate a which an unfavorable even occurs within a short period of time

42
Q

Hazard Ratio formula

A

Hazard rate of txm drop / HR rate of control group

43
Q

Odds Ratio and Hazard Ratio interoperation

A

OR/HR = 1 = event rate is same in txm/control arms, no advantage to txm

OR/HR < 1 = event rate is lower in txm group than control

OR/HR > 1 = event rate is higher in txm group than control

44
Q

When is T test used

A

used when endpoint has continuous data and normal distributed

when single sample group = one sample T test
when single sample group used for pre/post measurement (pt serves as own control) = paired T test

When study has 2 independent variables = student T-test

45
Q

When is ANOVA or F-test used

A

Used for continuous data

when using continuous data with 3 or more samples or groups

46
Q

What test is used for nominal or ordinal data

A

Chi square test

ie. Assessing difference in mortality between 2 groups or pain scores based on pain scale

47
Q

Correlation is….

A

technique used to determine if one variable changes or is related to another variable

when independent causes dependent to increase = positive correlation
when independent causes dependent to decrease = negative

correlation doesn’t prove causal relationships

48
Q

Regression is….

A

used to describe relationship between a depends variable and one or more independent

regression is common in observational studies where researchers need to assess multiple independent variables or need to control for many confounding factors

49
Q

Sensitivity vs Specificity

A

Sensitivity = how effectively test identifies pts with condition
100% sensitivity = test will be positive in all pts with condition

Specificity = how effectively test identifies pts without condition
100% specificity = test will be negative in all pts without condition

50
Q

Sensitivity formula……

A

(A / A + C) X 100

A = # that have condition w/ positive test result
C = # that have condition w/ negative test result

51
Q

Specificity formula…..

A

( D / B + D) X 100

D = # without condition with a negative test result
B = # without condition with a positive test result

52
Q

Intention to treat analysis

A

include data for all pts original allocated to each txm group, even if the patient did not complete the trial according to study protocol

53
Q

Per Protocol analysis

A

conducted for subset of trial population who completed the study according toe the protocol

54
Q

Equivalence trials

A

attempt to demonstrate new txm has roughly same effect as old txm

55
Q

Non-inferiority trials

A

attempt to demonstrate new txm is no worse than current standard based on predefined non-inferiority (delta) margin

delta margin is minimal difference in effect btw 2 groups that is considered clinically acceptable based on previous research

56
Q

When are forest plots used

A

often in meta-analysis, when multiple studies results are pooled into a single study

57
Q

Case control study Benefits & Limitations

A

Info: compares pts with disease vs without, retrospective

Benefits: data easy to get, less $$ than RCT, good for looking at outcomes in unethical interventions

Limitations: cause and effect cant reliably by determined

58
Q

Cohort Study Benefits & Limitations

A

Info: compares outcomes of group of pts exposed and not exposed to txm, follows prospectively

Benefits: good for looking at outcomes when intervention would be unethical

Limitations: more time consuming and $$$ than retrospective, can be influence by confounders (other factors that affect outcome)

59
Q

Case Report/ Case Series Benefits & Limitations

A

Info: signe patient = report, few patients = series

Benefit: Identify new diseases, drug SE or potential uses, can generate hypothesis for other studies

Limitations: conclusions cant be drawn from single or few cases

60
Q

Randomized control trial Benefits & Limitations

A

Info: pts randomized and sometimes blinded to txm groups

Benefit: Less potential bias, preferred study to determine cause/effect/ superity

Limitations: $$$ and time consuming, hard to reflect real life scenarios

61
Q

Crossover RCT info

A

pts receive treatment A first, then switch to txm B and second group does opposite

Benefit: act as own control, minimize confounders
Limit: washout period req

62
Q

Meta-analysis Benefits & Limitations

A

Info: combines results from multiple studies to come to conclusion that has more statistical power

Benefit: smaller studies can be pooled, instead of making large study

Limit: studies may no be uniform in size/inclusion/exclusion etc

63
Q

Systemic review article info

A

summary of clinical literature that focuses on specific topic or question

Benefit: cheap, studies already exist

64
Q

Direct Medical costs

A

Drug prep, admin, etc
Inpatient direct costs = hospital bed, staff, procedures etc
Outpatient direct costs = office/clinic visits

65
Q

Direct Non medical costs

A

traveling/lodging to hospital/clinic
household costs like childcare, etc
home health aides, etc

66
Q

Indirect costs

A

Lost work time
Low work productivity
morbidity, costs from having disease
mortality = death

67
Q

Intangible costs

A

pain, suffering, anxiety etc

68
Q

Incremental cost-effectiveness ratios

A

represents change in costs and outcomes when 2 txm alternatives are compared

ex. Drug A $200, 5 txm success vs Drub B $300, 7txm success

$300- $200 / 7 - 5 = $100/2 = $50

Drug B costs $50 more relative to Drug A for each additional txm success

69
Q

Cost minimization analysis

A

used when 2 or more interventions have demonstrated equivalence in outcoems and the costs of each intervention are being compared

70
Q

Cost benefit analysis

A

systemic process for calculating and comparing benefits of an intervention in terms of monetary units (dollars)

71
Q

Cost effectiveness analysis

A

used to compare clinical effects of two or more interventions to the respective costs

advantages = outcomes easier to quantify
disadvantages = inability to directly compare different types of outcomes

72
Q

Cost utility analysis

A

specialized form of CEA that includes quality of life competent of morbidity assessments, usually use QALY and DALYs

73
Q
A

NAPLEX review 2024 RXPrep Book (78 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions