Biostatistics Flashcards

(73 cards)

1
Q

two types of continuous data

A

Ratio and interval data

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2
Q

Ratio data

A

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

example: age, height, weight, time, BP

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3
Q

Interval data

A

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

example: temp

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4
Q

two types of Discrete (Categorical) data

A

nominal and ordinal

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5
Q

Nominal data

A

sorted into arbitrary categories

males/females

known as yes/no data

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6
Q

ordinal data

A

ranked and has a logical order

ie. pain scale, 1-10

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7
Q

Which data is mean preferred

A

continuous data that is normally distributed

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8
Q

Which data is median preferred

A

continuous data that is no normal distributed

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9
Q

Which data is mode preferred

A

nominal data

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10
Q

Percent of values within 1 SD? 2 SD?

A

1 SD = 65%
2 SD = 95%

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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

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12
Q

Independent vs dependent variable

A

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

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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

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14
Q

Alternative hypothesis

A

states that there is a statistically significant difference between the groups

what the researcher hopes to prove or accept

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15
Q

Alpha

A

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

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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

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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

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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

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19
Q

Narrow vs Wide Confidence interval

A

Narrow = high precision
Wide = lower precision

narrow is preferred

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20
Q

Type 1 error

A

False positive

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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

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22
Q

Type 2 error

A

False negative

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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

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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

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25
Power is determined by....
number of outcome values collected, difference in outcome rates between groups and significance (alpha) lvl larger sample size = increases study power
26
Relative risk (Risk ratio) is....
ratio of risk in exposed group (txm) divided by risk in control group
27
Risk is....
number of subjects in group with an unfavorable event / total number of subjects in group
28
Risk Ratio is...
risk in txm group / risk in control group
29
Risk Ratio interpretation
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
30
Relative risk reduction....
indicates how much the risk is reduced in the txm group compared to the control group 1 - Risk Ratio = RRR
31
RRR interpretation of 43%
XXXXX patients were 43% less likely to have YYYYY than placebo-treated patients
32
Absolute risk reduction
includes the reduction in risk and incidence rate of the outcome ARR = % risk in control group - % risk in txm group
33
ARR interpretation of 12%
12 out of every 100 patients will benefit from txm or For every 100 patients tx with XXX, 12 fever will have YYYYY
34
Number needed to treat
number of patients who need to be treated for a certain period of time for one patient to benefit 1/ ARR
35
Number needed to treat interpretation, NNT = 9
For eery 9 pts who receive XXX, YYYY is prevented in 1 patient
36
Number needed to harm
number of patients need to be treated for one patient to experience harm same formula, 1/ ARR
37
Number needed to harm interpretation, NNH = 90
1 patient will be harmed for every 90 patients treated with XXX instead of placebo
38
Which studies are not suitable for relative risk calculations
Case control studies use Odds ratio
39
Odds Ratio formula
Exposure/txm | Outcome present | Outcome Absent | -------------------------------------------------------------------------------- Present | A | B. | -------------------------------------------------------------------------------- Absent. |. C. |. D. | Formula = AD/ BC
40
Interpreting Odds ratio of 1.23
XXXXXX is associated with 25% increased risk of YYYYYY
41
Hazard ratio
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
Hazard Ratio formula
Hazard rate of txm drop / HR rate of control group
43
Odds Ratio and Hazard Ratio interoperation
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
When is T test used
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
When is ANOVA or F-test used
Used for continuous data when using continuous data with 3 or more samples or groups
46
What test is used for nominal or ordinal data
Chi square test ie. Assessing difference in mortality between 2 groups or pain scores based on pain scale
47
Correlation is....
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
Regression is....
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
Sensitivity vs Specificity
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
Sensitivity formula......
(A / A + C) X 100 A = # that have condition w/ positive test result C = # that have condition w/ negative test result
51
Specificity formula.....
( D / B + D) X 100 D = # without condition with a negative test result B = # without condition with a positive test result
52
Intention to treat analysis
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
Per Protocol analysis
conducted for subset of trial population who completed the study according toe the protocol
54
Equivalence trials
attempt to demonstrate new txm has roughly same effect as old txm
55
Non-inferiority trials
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
When are forest plots used
often in meta-analysis, when multiple studies results are pooled into a single study
57
Case control study Benefits & Limitations
Info: compares pts with disease vs without, retrospective Benefits: data easy to get, less $$ than RCT, good for looking at outcomes in unethical interventions Limitations: cause and effect cant reliably by determined
58
Cohort Study Benefits & Limitations
Info: compares outcomes of group of pts exposed and not exposed to txm, follows prospectively Benefits: good for looking at outcomes when intervention would be unethical Limitations: more time consuming and $$$ than retrospective, can be influence by confounders (other factors that affect outcome)
59
Case Report/ Case Series Benefits & Limitations
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
Randomized control trial Benefits & Limitations
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
Crossover RCT info
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
Meta-analysis Benefits & Limitations
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
Systemic review article info
summary of clinical literature that focuses on specific topic or question Benefit: cheap, studies already exist
64
Direct Medical costs
Drug prep, admin, etc Inpatient direct costs = hospital bed, staff, procedures etc Outpatient direct costs = office/clinic visits
65
Direct Non medical costs
traveling/lodging to hospital/clinic household costs like childcare, etc home health aides, etc
66
Indirect costs
Lost work time Low work productivity morbidity, costs from having disease mortality = death
67
Intangible costs
pain, suffering, anxiety etc
68
Incremental cost-effectiveness ratios
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
Cost minimization analysis
used when 2 or more interventions have demonstrated equivalence in outcoems and the costs of each intervention are being compared
70
Cost benefit analysis
systemic process for calculating and comparing benefits of an intervention in terms of monetary units (dollars)
71
Cost effectiveness analysis
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
Cost utility analysis
specialized form of CEA that includes quality of life competent of morbidity assessments, usually use QALY and DALYs
73